Statsmodels | Docs4dev

Table of Contents

ANOVA
- AnovaRM.fit()
- stats.anova.AnovaRM()
- stats.anova.anova_lm()
Contingency tables
- SquareTable.chi2_contribs()
- SquareTable.cumulative_log_oddsratios()
- SquareTable.cumulative_oddsratios()
- SquareTable.fittedvalues()
- SquareTable.from_data()
- SquareTable.homogeneity()
- SquareTable.independence_probabilities()
- SquareTable.local_log_oddsratios()
- SquareTable.local_oddsratios()
- SquareTable.marginal_probabilities()
- SquareTable.resid_pearson()
- SquareTable.standardized_resids()
- SquareTable.summary()
- SquareTable.symmetry()
- SquareTable.test_nominal_association()
- SquareTable.test_ordinal_association()
- stats.contingency_tables.cochrans_q()
- stats.contingency_tables.mcnemar()
- stats.contingency_tables.SquareTable()
- stats.contingency_tables.StratifiedTable()
- stats.contingency_tables.Table()
- stats.contingency_tables.Table2x2()
- StratifiedTable.from_data()
- StratifiedTable.logodds_pooled()
- StratifiedTable.logodds_pooled_confint()
- StratifiedTable.logodds_pooled_se()
- StratifiedTable.oddsratio_pooled()
- StratifiedTable.oddsratio_pooled_confint()
- StratifiedTable.risk_pooled()
- StratifiedTable.summary()
- StratifiedTable.test_equal_odds()
- StratifiedTable.test_null_odds()
- Table.chi2_contribs()
- Table.cumulative_log_oddsratios()
- Table.cumulative_oddsratios()
- Table.fittedvalues()
- Table.from_data()
- Table.independence_probabilities()
- Table.local_log_oddsratios()
- Table.local_oddsratios()
- Table.marginal_probabilities()
- Table.resid_pearson()
- Table.standardized_resids()
- Table.test_nominal_association()
- Table.test_ordinal_association()
- Table2x2.chi2_contribs()
- Table2x2.cumulative_log_oddsratios()
- Table2x2.cumulative_oddsratios()
- Table2x2.fittedvalues()
- Table2x2.from_data()
- Table2x2.homogeneity()
- Table2x2.independence_probabilities()
- Table2x2.local_log_oddsratios()
- Table2x2.local_oddsratios()
- Table2x2.log_oddsratio()
- Table2x2.log_oddsratio_confint()
- Table2x2.log_oddsratio_pvalue()
- Table2x2.log_oddsratio_se()
- Table2x2.log_riskratio()
- Table2x2.log_riskratio_confint()
- Table2x2.log_riskratio_pvalue()
- Table2x2.log_riskratio_se()
- Table2x2.marginal_probabilities()
- Table2x2.oddsratio()
- Table2x2.oddsratio_confint()
- Table2x2.oddsratio_pvalue()
- Table2x2.resid_pearson()
- Table2x2.riskratio()
- Table2x2.riskratio_confint()
- Table2x2.riskratio_pvalue()
- Table2x2.standardized_resids()
- Table2x2.summary()
- Table2x2.symmetry()
- Table2x2.test_nominal_association()
- Table2x2.test_ordinal_association()
Distributions
- ACSkewT_gen.cdf()
- ACSkewT_gen.entropy()
- ACSkewT_gen.expect()
- ACSkewT_gen.fit()
- ACSkewT_gen.fit_loc_scale()
- ACSkewT_gen.freeze()
- ACSkewT_gen.interval()
- ACSkewT_gen.isf()
- ACSkewT_gen.logcdf()
- ACSkewT_gen.logpdf()
- ACSkewT_gen.logsf()
- ACSkewT_gen.mean()
- ACSkewT_gen.median()
- ACSkewT_gen.moment()
- ACSkewT_gen.nnlf()
- ACSkewT_gen.pdf()
- ACSkewT_gen.ppf()
- ACSkewT_gen.rvs()
- ACSkewT_gen.sf()
- ACSkewT_gen.stats()
- ACSkewT_gen.std()
- ACSkewT_gen.var()
- distributions.empirical_distribution.ECDF()
- distributions.empirical_distribution.monotone_fn_inverter()
- distributions.empirical_distribution.StepFunction()
- ExpTransf_gen.cdf()
- ExpTransf_gen.entropy()
- ExpTransf_gen.expect()
- ExpTransf_gen.fit()
- ExpTransf_gen.fit_loc_scale()
- ExpTransf_gen.freeze()
- ExpTransf_gen.interval()
- ExpTransf_gen.isf()
- ExpTransf_gen.logcdf()
- ExpTransf_gen.logpdf()
- ExpTransf_gen.logsf()
- ExpTransf_gen.mean()
- ExpTransf_gen.median()
- ExpTransf_gen.moment()
- ExpTransf_gen.nnlf()
- ExpTransf_gen.pdf()
- ExpTransf_gen.ppf()
- ExpTransf_gen.rvs()
- ExpTransf_gen.sf()
- ExpTransf_gen.stats()
- ExpTransf_gen.std()
- ExpTransf_gen.var()
- LogTransf_gen.cdf()
- LogTransf_gen.entropy()
- LogTransf_gen.expect()
- LogTransf_gen.fit()
- LogTransf_gen.fit_loc_scale()
- LogTransf_gen.freeze()
- LogTransf_gen.interval()
- LogTransf_gen.isf()
- LogTransf_gen.logcdf()
- LogTransf_gen.logpdf()
- LogTransf_gen.logsf()
- LogTransf_gen.mean()
- LogTransf_gen.median()
- LogTransf_gen.moment()
- LogTransf_gen.nnlf()
- LogTransf_gen.pdf()
- LogTransf_gen.ppf()
- LogTransf_gen.rvs()
- LogTransf_gen.sf()
- LogTransf_gen.stats()
- LogTransf_gen.std()
- LogTransf_gen.var()
- NormExpan_gen.cdf()
- NormExpan_gen.entropy()
- NormExpan_gen.expect()
- NormExpan_gen.fit()
- NormExpan_gen.fit_loc_scale()
- NormExpan_gen.freeze()
- NormExpan_gen.interval()
- NormExpan_gen.isf()
- NormExpan_gen.logcdf()
- NormExpan_gen.logpdf()
- NormExpan_gen.logsf()
- NormExpan_gen.mean()
- NormExpan_gen.median()
- NormExpan_gen.moment()
- NormExpan_gen.nnlf()
- NormExpan_gen.pdf()
- NormExpan_gen.ppf()
- NormExpan_gen.rvs()
- NormExpan_gen.sf()
- NormExpan_gen.stats()
- NormExpan_gen.std()
- NormExpan_gen.var()
- sandbox.distributions.extras.ACSkewT_gen
- sandbox.distributions.extras.mvnormcdf()
- sandbox.distributions.extras.mvstdnormcdf()
- sandbox.distributions.extras.NormExpan_gen()
- sandbox.distributions.extras.pdf_moments()
- sandbox.distributions.extras.pdf_moments_st()
- sandbox.distributions.extras.pdf_mvsk()
- sandbox.distributions.extras.skewnorm2
- sandbox.distributions.extras.SkewNorm2_gen()
- sandbox.distributions.extras.SkewNorm_gen
- sandbox.distributions.transformed.absnormalg
- sandbox.distributions.transformed.ExpTransf_gen()
- sandbox.distributions.transformed.invdnormalg
- sandbox.distributions.transformed.loggammaexpg
- sandbox.distributions.transformed.lognormalg
- sandbox.distributions.transformed.LogTransf_gen()
- sandbox.distributions.transformed.negsquarenormalg
- sandbox.distributions.transformed.SquareFunc
- sandbox.distributions.transformed.squarenormalg
- sandbox.distributions.transformed.squaretg
- sandbox.distributions.transformed.TransfTwo_gen()
- sandbox.distributions.transformed.Transf_gen()
- SkewNorm2_gen.cdf()
- SkewNorm2_gen.entropy()
- SkewNorm2_gen.expect()
- SkewNorm2_gen.fit()
- SkewNorm2_gen.fit_loc_scale()
- SkewNorm2_gen.freeze()
- SkewNorm2_gen.interval()
- SkewNorm2_gen.isf()
- SkewNorm2_gen.logcdf()
- SkewNorm2_gen.logpdf()
- SkewNorm2_gen.logsf()
- SkewNorm2_gen.mean()
- SkewNorm2_gen.median()
- SkewNorm2_gen.moment()
- SkewNorm2_gen.nnlf()
- SkewNorm2_gen.pdf()
- SkewNorm2_gen.ppf()
- SkewNorm2_gen.rvs()
- SkewNorm2_gen.sf()
- SkewNorm2_gen.stats()
- SkewNorm2_gen.std()
- SkewNorm2_gen.var()
- SkewNorm_gen.cdf()
- SkewNorm_gen.entropy()
- SkewNorm_gen.expect()
- SkewNorm_gen.fit()
- SkewNorm_gen.fit_loc_scale()
- SkewNorm_gen.freeze()
- SkewNorm_gen.interval()
- SkewNorm_gen.isf()
- SkewNorm_gen.logcdf()
- SkewNorm_gen.logpdf()
- SkewNorm_gen.logsf()
- SkewNorm_gen.mean()
- SkewNorm_gen.median()
- SkewNorm_gen.moment()
- SkewNorm_gen.nnlf()
- SkewNorm_gen.pdf()
- SkewNorm_gen.ppf()
- SkewNorm_gen.rvs()
- SkewNorm_gen.sf()
- SkewNorm_gen.stats()
- SkewNorm_gen.std()
- SkewNorm_gen.var()
- SquareFunc.derivminus()
- SquareFunc.derivplus()
- SquareFunc.inverseminus()
- SquareFunc.inverseplus()
- SquareFunc.squarefunc()
- TransfTwo_gen.cdf()
- TransfTwo_gen.entropy()
- TransfTwo_gen.expect()
- TransfTwo_gen.fit()
- TransfTwo_gen.fit_loc_scale()
- TransfTwo_gen.freeze()
- TransfTwo_gen.interval()
- TransfTwo_gen.isf()
- TransfTwo_gen.logcdf()
- TransfTwo_gen.logpdf()
- TransfTwo_gen.logsf()
- TransfTwo_gen.mean()
- TransfTwo_gen.median()
- TransfTwo_gen.moment()
- TransfTwo_gen.nnlf()
- TransfTwo_gen.pdf()
- TransfTwo_gen.ppf()
- TransfTwo_gen.rvs()
- TransfTwo_gen.sf()
- TransfTwo_gen.stats()
- TransfTwo_gen.std()
- TransfTwo_gen.var()
- Transf_gen.cdf()
- Transf_gen.entropy()
- Transf_gen.expect()
- Transf_gen.fit()
- Transf_gen.fit_loc_scale()
- Transf_gen.freeze()
- Transf_gen.interval()
- Transf_gen.isf()
- Transf_gen.logcdf()
- Transf_gen.logpdf()
- Transf_gen.logsf()
- Transf_gen.mean()
- Transf_gen.median()
- Transf_gen.moment()
- Transf_gen.nnlf()
- Transf_gen.pdf()
- Transf_gen.ppf()
- Transf_gen.rvs()
- Transf_gen.sf()
- Transf_gen.stats()
- Transf_gen.std()
- Transf_gen.var()
Empirical Likelihood
- DescStatMV.ci_corr()
- DescStatMV.mv_mean_contour()
- DescStatMV.mv_test_mean()
- DescStatMV.test_corr()
- DescStatUV.ci_kurt()
- DescStatUV.ci_mean()
- DescStatUV.ci_skew()
- DescStatUV.ci_var()
- DescStatUV.plot_contour()
- DescStatUV.test_joint_skew_kurt()
- DescStatUV.test_kurt()
- DescStatUV.test_mean()
- DescStatUV.test_skew()
- DescStatUV.test_var()
- emplike.descriptive.DescStat()
- emplike.descriptive.DescStatMV()
- emplike.descriptive.DescStatUV()
Examples
- Example: Autoregressive Moving Average (ARMA): Artificial data
- Example: Autoregressive Moving Average (ARMA): Sunspots data
- Example: Autoregressive Moving Average (ARMA): Sunspots data
- Example: Contrasts Overview
- Example: Dates in timeseries models
- Example: Detrending, Stylized Facts and the Business Cycle
- Example: Discrete Choice Models
- Example: Discrete Choice Models Overview
- Example: Dynamic factors and coincident indices
- Example: Formulas: Fitting models using R-style formulas
- Example: Generalized Least Squares
- Example: Generalized Linear Models
- Example: Generalized Linear Models (Formula)
- Example: Interactions and ANOVA
- Example: Kernel Density Estimation
- Example: Linear Mixed Effects Models
- Example: M-Estimators for Robust Linear Modeling
- Example: Markov switching autoregression models
- Example: Markov switching dynamic regression models
- Example: Maximum Likelihood Estimation (Generic models)
- Example: Ordinary Least Squares
- Example: Plot Interaction of Categorical Factors
- Example: Prediction (out of sample)
- Example: Quantile regression
- Example: Recursive least squares
- Example: Regression diagnostics
- Example: Regression Plots
- Example: Robust Linear Models
- Example: SARIMAX: Introduction
- Example: SARIMAX: Model selection, missing data
- Example: State space modeling: Local Linear Trends
- Example: Statsmodels Examples
- Example: Time Series Filters
- Example: Trends and cycles in unemployment
- Example: VARMAX models
- Example: Weighted Least Squares
Generalized Estimating Equations
- Autoregressive.covariance_matrix()
- Autoregressive.covariance_matrix_solve()
- Autoregressive.initialize()
- Autoregressive.summary()
- Autoregressive.update()
- CovStruct.covariance_matrix()
- CovStruct.covariance_matrix_solve()
- CovStruct.initialize()
- CovStruct.summary()
- CovStruct.update()
- Exchangeable.covariance_matrix()
- Exchangeable.covariance_matrix_solve()
- Exchangeable.initialize()
- Exchangeable.summary()
- Exchangeable.update()
- GEE.cluster_list()
- GEE.estimate_scale()
- GEE.fit()
- GEE.from_formula()
- GEE.mean_deriv()
- GEE.mean_deriv_exog()
- GEE.predict()
- GEE.update_cached_means()
- GEEMargins.conf_int()
- GEEMargins.get_margeff()
- GEEMargins.pvalues()
- GEEMargins.summary()
- GEEMargins.summary_frame()
- GEEMargins.tvalues()
- GEEResults.bse()
- GEEResults.centered_resid()
- GEEResults.conf_int()
- GEEResults.cov_params()
- GEEResults.fittedvalues()
- GEEResults.f_test()
- GEEResults.get_margeff()
- GEEResults.initialize()
- GEEResults.llf()
- GEEResults.load()
- GEEResults.normalized_cov_params()
- GEEResults.params_sensitivity()
- GEEResults.plot_added_variable()
- GEEResults.plot_ceres_residuals()
- GEEResults.plot_isotropic_dependence()
- GEEResults.plot_partial_residuals()
- GEEResults.predict()
- GEEResults.pvalues()
- GEEResults.remove_data()
- GEEResults.resid()
- GEEResults.resid_anscombe()
- GEEResults.resid_centered()
- GEEResults.resid_centered_split()
- GEEResults.resid_deviance()
- GEEResults.resid_pearson()
- GEEResults.resid_response()
- GEEResults.resid_split()
- GEEResults.resid_working()
- GEEResults.save()
- GEEResults.sensitivity_params()
- GEEResults.split_centered_resid()
- GEEResults.split_resid()
- GEEResults.standard_errors()
- GEEResults.summary()
- GEEResults.tvalues()
- GEEResults.t_test()
- GEEResults.t_test_pairwise()
- GEEResults.wald_test()
- GEEResults.wald_test_terms()
- genmod.cov_struct.Autoregressive()
- genmod.cov_struct.CovStruct()
- genmod.cov_struct.Exchangeable
- genmod.cov_struct.GlobalOddsRatio()
- genmod.cov_struct.Independence()
- genmod.cov_struct.Nested()
- genmod.generalized_estimating_equations.GEE()
- genmod.generalized_estimating_equations.GEEMargins()
- genmod.generalized_estimating_equations.GEEResults()
- GlobalOddsRatio.covariance_matrix()
- GlobalOddsRatio.covariance_matrix_solve()
- GlobalOddsRatio.get_eyy()
- GlobalOddsRatio.initialize()
- GlobalOddsRatio.observed_crude_oddsratio()
- GlobalOddsRatio.pooled_odds_ratio()
- GlobalOddsRatio.summary()
- GlobalOddsRatio.update()
- Independence.covariance_matrix()
- Independence.covariance_matrix_solve()
- Independence.initialize()
- Independence.summary()
- Independence.update()
- Nested.covariance_matrix()
- Nested.covariance_matrix_solve()
- Nested.initialize()
- Nested.summary()
- Nested.update()
Generalized Linear Mixed Effects Models
- BayesMixedGLMResults.random_effects()
- BayesMixedGLMResults.summary()
- BinomialBayesMixedGLM.fit()
- BinomialBayesMixedGLM.fit_map()
- BinomialBayesMixedGLM.fit_vb()
- BinomialBayesMixedGLM.from_formula()
- BinomialBayesMixedGLM.logposterior()
- BinomialBayesMixedGLM.logposterior_grad()
- BinomialBayesMixedGLM.predict()
- BinomialBayesMixedGLM.vb_elbo()
- BinomialBayesMixedGLM.vb_elbo_base()
- BinomialBayesMixedGLM.vb_elbo_grad()
- BinomialBayesMixedGLM.vb_elbo_grad_base()
- genmod.bayes_mixed_glm.BayesMixedGLMResults()
- genmod.bayes_mixed_glm.BinomialBayesMixedGLM()
- genmod.bayes_mixed_glm.PoissonBayesMixedGLM()
- PoissonBayesMixedGLM.fit()
- PoissonBayesMixedGLM.fit_map()
- PoissonBayesMixedGLM.fit_vb()
- PoissonBayesMixedGLM.from_formula()
- PoissonBayesMixedGLM.logposterior()
- PoissonBayesMixedGLM.logposterior_grad()
- PoissonBayesMixedGLM.predict()
- PoissonBayesMixedGLM.vb_elbo()
- PoissonBayesMixedGLM.vb_elbo_base()
- PoissonBayesMixedGLM.vb_elbo_grad()
- PoissonBayesMixedGLM.vb_elbo_grad_base()
Generalized Linear Models
- Binomial.deviance()
- Binomial.fitted()
- Binomial.initialize()
- Binomial.loglike()
- Binomial.loglike_obs()
- Binomial.predict()
- Binomial.resid_anscombe()
- Binomial.resid_dev()
- Binomial.starting_mu()
- Binomial.weights()
- cauchy.deriv()
- cauchy.deriv2()
- cauchy.inverse()
- cauchy.inverse_deriv()
- CDFLink.deriv()
- CDFLink.deriv2()
- CDFLink.inverse()
- CDFLink.inverse_deriv()
- CLogLog.deriv()
- CLogLog.deriv2()
- CLogLog.inverse()
- CLogLog.inverse_deriv()
- Family.deviance()
- Family.fitted()
- Family.loglike()
- Family.loglike_obs()
- Family.predict()
- Family.resid_anscombe()
- Family.resid_dev()
- Family.starting_mu()
- Family.weights()
- Gamma.deviance()
- Gamma.fitted()
- Gamma.loglike()
- Gamma.loglike_obs()
- Gamma.predict()
- Gamma.resid_anscombe()
- Gamma.resid_dev()
- Gamma.starting_mu()
- Gamma.weights()
- Gaussian.deviance()
- Gaussian.fitted()
- Gaussian.loglike()
- Gaussian.loglike_obs()
- Gaussian.predict()
- Gaussian.resid_anscombe()
- Gaussian.resid_dev()
- Gaussian.starting_mu()
- Gaussian.weights()
- genmod.families.family.Binomial()
- genmod.families.family.Family()
- genmod.families.family.Gamma()
- genmod.families.family.Gaussian()
- genmod.families.family.InverseGaussian()
- genmod.families.family.NegativeBinomial()
- genmod.families.family.Poisson()
- genmod.families.family.Tweedie()
- genmod.families.links.cauchy
- genmod.families.links.CDFLink()
- genmod.families.links.CLogLog
- genmod.families.links.identity
- genmod.families.links.inverse_power
- genmod.families.links.inverse_squared
- genmod.families.links.Link
- genmod.families.links.Log
- genmod.families.links.Logit
- genmod.families.links.nbinom()
- genmod.families.links.NegativeBinomial()
- genmod.families.links.Power()
- genmod.families.links.probit()
- genmod.generalized_linear_model.GLM()
- genmod.generalized_linear_model.GLMResults()
- genmod.generalized_linear_model.PredictionResults()
- GLM.estimate_scale()
- GLM.estimate_tweedie_power()
- GLM.fit()
- GLM.fit_constrained()
- GLM.fit_regularized()
- GLM.from_formula()
- GLM.get_distribution()
- GLM.hessian()
- GLM.hessian_factor()
- GLM.information()
- GLM.initialize()
- GLM.loglike()
- GLM.loglike_mu()
- GLM.predict()
- GLM.score()
- GLM.score_factor()
- GLM.score_obs()
- GLM.score_test()
- GLMResults.aic()
- GLMResults.bic()
- GLMResults.bse()
- GLMResults.conf_int()
- GLMResults.cov_params()
- GLMResults.deviance()
- GLMResults.fittedvalues()
- GLMResults.f_test()
- GLMResults.get_prediction()
- GLMResults.initialize()
- GLMResults.llf()
- GLMResults.llnull()
- GLMResults.load()
- GLMResults.mu()
- GLMResults.normalized_cov_params()
- GLMResults.null()
- GLMResults.null_deviance()
- GLMResults.pearson_chi2()
- GLMResults.plot_added_variable()
- GLMResults.plot_ceres_residuals()
- GLMResults.plot_partial_residuals()
- GLMResults.predict()
- GLMResults.pvalues()
- GLMResults.remove_data()
- GLMResults.resid_anscombe()
- GLMResults.resid_anscombe_scaled()
- GLMResults.resid_anscombe_unscaled()
- GLMResults.resid_deviance()
- GLMResults.resid_pearson()
- GLMResults.resid_response()
- GLMResults.resid_working()
- GLMResults.save()
- GLMResults.summary()
- GLMResults.summary2()
- GLMResults.tvalues()
- GLMResults.t_test()
- GLMResults.t_test_pairwise()
- GLMResults.wald_test()
- GLMResults.wald_test_terms()
- identity.deriv()
- identity.deriv2()
- identity.inverse()
- identity.inverse_deriv()
- InverseGaussian.deviance()
- InverseGaussian.fitted()
- InverseGaussian.loglike()
- InverseGaussian.loglike_obs()
- InverseGaussian.predict()
- InverseGaussian.resid_anscombe()
- InverseGaussian.resid_dev()
- InverseGaussian.starting_mu()
- InverseGaussian.weights()
- inverse_power.deriv()
- inverse_power.deriv2()
- inverse_power.inverse()
- inverse_power.inverse_deriv()
- inverse_squared.deriv()
- inverse_squared.deriv2()
- inverse_squared.inverse()
- inverse_squared.inverse_deriv()
- Link.deriv()
- Link.deriv2()
- Link.inverse()
- Link.inverse_deriv()
- Log.deriv()
- Log.deriv2()
- Log.inverse()
- Log.inverse_deriv()
- Logit.deriv()
- Logit.deriv2()
- Logit.inverse()
- Logit.inverse_deriv()
- nbinom.deriv()
- nbinom.deriv2()
- nbinom.inverse()
- nbinom.inverse_deriv()
- NegativeBinomial.deriv()
- NegativeBinomial.deriv2()
- NegativeBinomial.deviance()
- NegativeBinomial.fitted()
- NegativeBinomial.inverse()
- NegativeBinomial.inverse_deriv()
- NegativeBinomial.loglike()
- NegativeBinomial.loglike_obs()
- NegativeBinomial.predict()
- NegativeBinomial.resid_anscombe()
- NegativeBinomial.resid_dev()
- NegativeBinomial.starting_mu()
- NegativeBinomial.weights()
- Poisson.deviance()
- Poisson.fitted()
- Poisson.loglike()
- Poisson.loglike_obs()
- Poisson.predict()
- Poisson.resid_anscombe()
- Poisson.resid_dev()
- Poisson.starting_mu()
- Poisson.weights()
- Power.deriv()
- Power.deriv2()
- Power.inverse()
- Power.inverse_deriv()
- PredictionResults.conf_int()
- PredictionResults.summary_frame()
- PredictionResults.t_test()
- probit.deriv()
- probit.deriv2()
- probit.inverse()
- probit.inverse_deriv()
- Tweedie.deviance()
- Tweedie.fitted()
- Tweedie.loglike()
- Tweedie.loglike_obs()
- Tweedie.predict()
- Tweedie.resid_anscombe()
- Tweedie.resid_dev()
- Tweedie.starting_mu()
- Tweedie.weights()
Generalized Method of Moments
- GMM.calc_weightmatrix()
- GMM.fit()
- GMM.fitgmm()
- GMM.fitgmm_cu()
- GMM.fititer()
- GMM.from_formula()
- GMM.gmmobjective()
- GMM.gmmobjective_cu()
- GMM.gradient_momcond()
- GMM.momcond_mean()
- GMM.predict()
- GMM.score()
- GMM.score_cu()
- GMM.set_param_names()
- GMM.start_weights()
- GMMResults.bse()
- GMMResults.calc_cov_params()
- GMMResults.compare_j()
- GMMResults.conf_int()
- GMMResults.cov_params()
- GMMResults.f_test()
- GMMResults.get_bse()
- GMMResults.initialize()
- GMMResults.jtest()
- GMMResults.jval()
- GMMResults.llf()
- GMMResults.load()
- GMMResults.normalized_cov_params()
- GMMResults.predict()
- GMMResults.pvalues()
- GMMResults.q()
- GMMResults.remove_data()
- GMMResults.save()
- GMMResults.summary()
- GMMResults.tvalues()
- GMMResults.t_test()
- GMMResults.t_test_pairwise()
- GMMResults.wald_test()
- GMMResults.wald_test_terms()
- IV2SLS.fit()
- IV2SLS.from_formula()
- IV2SLS.hessian()
- IV2SLS.information()
- IV2SLS.initialize()
- IV2SLS.loglike()
- IV2SLS.predict()
- IV2SLS.score()
- IV2SLS.whiten()
- IVGMM.calc_weightmatrix()
- IVGMM.fit()
- IVGMM.fitgmm()
- IVGMM.fitgmm_cu()
- IVGMM.fititer()
- IVGMM.fitstart()
- IVGMM.from_formula()
- IVGMM.get_error()
- IVGMM.gmmobjective()
- IVGMM.gmmobjective_cu()
- IVGMM.gradient_momcond()
- IVGMM.momcond()
- IVGMM.momcond_mean()
- IVGMM.predict()
- IVGMM.score()
- IVGMM.score_cu()
- IVGMM.set_param_names()
- IVGMM.start_weights()
- IVGMMResults.bse()
- IVGMMResults.calc_cov_params()
- IVGMMResults.compare_j()
- IVGMMResults.conf_int()
- IVGMMResults.cov_params()
- IVGMMResults.fittedvalues()
- IVGMMResults.f_test()
- IVGMMResults.get_bse()
- IVGMMResults.initialize()
- IVGMMResults.jtest()
- IVGMMResults.jval()
- IVGMMResults.llf()
- IVGMMResults.load()
- IVGMMResults.normalized_cov_params()
- IVGMMResults.predict()
- IVGMMResults.pvalues()
- IVGMMResults.q()
- IVGMMResults.remove_data()
- IVGMMResults.resid()
- IVGMMResults.save()
- IVGMMResults.ssr()
- IVGMMResults.summary()
- IVGMMResults.tvalues()
- IVGMMResults.t_test()
- IVGMMResults.t_test_pairwise()
- IVGMMResults.wald_test()
- IVGMMResults.wald_test_terms()
- IVRegressionResults.aic()
- IVRegressionResults.bic()
- IVRegressionResults.bse()
- IVRegressionResults.centered_tss()
- IVRegressionResults.compare_f_test()
- IVRegressionResults.compare_lm_test()
- IVRegressionResults.compare_lr_test()
- IVRegressionResults.condition_number()
- IVRegressionResults.conf_int()
- IVRegressionResults.cov_HC0()
- IVRegressionResults.cov_HC1()
- IVRegressionResults.cov_HC2()
- IVRegressionResults.cov_HC3()
- IVRegressionResults.cov_params()
- IVRegressionResults.eigenvals()
- IVRegressionResults.ess()
- IVRegressionResults.fittedvalues()
- IVRegressionResults.fvalue()
- IVRegressionResults.f_pvalue()
- IVRegressionResults.f_test()
- IVRegressionResults.get_prediction()
- IVRegressionResults.get_robustcov_results()
- IVRegressionResults.HC0_se()
- IVRegressionResults.HC1_se()
- IVRegressionResults.HC2_se()
- IVRegressionResults.HC3_se()
- IVRegressionResults.initialize()
- IVRegressionResults.llf()
- IVRegressionResults.load()
- IVRegressionResults.mse_model()
- IVRegressionResults.mse_resid()
- IVRegressionResults.mse_total()
- IVRegressionResults.nobs()
- IVRegressionResults.normalized_cov_params()
- IVRegressionResults.predict()
- IVRegressionResults.pvalues()
- IVRegressionResults.remove_data()
- IVRegressionResults.resid()
- IVRegressionResults.resid_pearson()
- IVRegressionResults.rsquared()
- IVRegressionResults.rsquared_adj()
- IVRegressionResults.save()
- IVRegressionResults.scale()
- IVRegressionResults.spec_hausman()
- IVRegressionResults.ssr()
- IVRegressionResults.summary()
- IVRegressionResults.summary2()
- IVRegressionResults.tvalues()
- IVRegressionResults.t_test()
- IVRegressionResults.t_test_pairwise()
- IVRegressionResults.uncentered_tss()
- IVRegressionResults.wald_test()
- IVRegressionResults.wald_test_terms()
- IVRegressionResults.wresid()
- LinearIVGMM.calc_weightmatrix()
- LinearIVGMM.fit()
- LinearIVGMM.fitgmm()
- LinearIVGMM.fitgmm_cu()
- LinearIVGMM.fititer()
- LinearIVGMM.fitstart()
- LinearIVGMM.from_formula()
- LinearIVGMM.get_error()
- LinearIVGMM.gmmobjective()
- LinearIVGMM.gmmobjective_cu()
- LinearIVGMM.gradient_momcond()
- LinearIVGMM.momcond()
- LinearIVGMM.momcond_mean()
- LinearIVGMM.predict()
- LinearIVGMM.score()
- LinearIVGMM.score_cu()
- LinearIVGMM.set_param_names()
- LinearIVGMM.start_weights()
- NonlinearIVGMM.calc_weightmatrix()
- NonlinearIVGMM.fit()
- NonlinearIVGMM.fitgmm()
- NonlinearIVGMM.fitgmm_cu()
- NonlinearIVGMM.fititer()
- NonlinearIVGMM.fitstart()
- NonlinearIVGMM.from_formula()
- NonlinearIVGMM.get_error()
- NonlinearIVGMM.gmmobjective()
- NonlinearIVGMM.gmmobjective_cu()
- NonlinearIVGMM.gradient_momcond()
- NonlinearIVGMM.jac_error()
- NonlinearIVGMM.jac_func()
- NonlinearIVGMM.momcond()
- NonlinearIVGMM.momcond_mean()
- NonlinearIVGMM.predict()
- NonlinearIVGMM.score()
- NonlinearIVGMM.score_cu()
- NonlinearIVGMM.set_param_names()
- NonlinearIVGMM.start_weights()
- sandbox.regression.gmm.GMM()
- sandbox.regression.gmm.GMMResults()
- sandbox.regression.gmm.IV2SLS()
- sandbox.regression.gmm.IVGMM()
- sandbox.regression.gmm.IVGMMResults()
- sandbox.regression.gmm.IVRegressionResults()
- sandbox.regression.gmm.LinearIVGMM()
- sandbox.regression.gmm.NonlinearIVGMM()
Graphics
- graphics.agreement.mean_diff_plot()
- graphics.boxplots.beanplot()
- graphics.boxplots.violinplot()
- graphics.correlation.plot_corr()
- graphics.correlation.plot_corr_grid()
- graphics.factorplots.interaction_plot()
- graphics.functional.banddepth()
- graphics.functional.fboxplot()
- graphics.functional.hdrboxplot()
- graphics.functional.rainbowplot()
- graphics.gofplots.ProbPlot()
- graphics.gofplots.qqline()
- graphics.gofplots.qqplot()
- graphics.gofplots.qqplot_2samples()
- graphics.mosaicplot.mosaic()
- graphics.plot_grids.scatter_ellipse()
- graphics.regressionplots.abline_plot()
- graphics.regressionplots.influence_plot()
- graphics.regressionplots.plot_ccpr()
- graphics.regressionplots.plot_fit()
- graphics.regressionplots.plot_leverage_resid2()
- graphics.regressionplots.plot_partregress()
- graphics.regressionplots.plot_regress_exog()
- graphics.tsaplots.month_plot()
- graphics.tsaplots.plot_acf()
- graphics.tsaplots.plot_pacf()
- graphics.tsaplots.quarter_plot()
- ProbPlot.ppplot()
- ProbPlot.probplot()
- ProbPlot.qqplot()
- ProbPlot.sample_percentiles()
- ProbPlot.sample_quantiles()
- ProbPlot.sorted_data()
- ProbPlot.theoretical_percentiles()
- ProbPlot.theoretical_quantiles()
Input-Output
- iolib.foreign.genfromdta()
- iolib.foreign.savetxt()
- iolib.foreign.StataReader()
- iolib.foreign.StataWriter()
- iolib.smpickle.load_pickle()
- iolib.smpickle.save_pickle()
- iolib.summary.Summary
- iolib.summary2.Summary
- iolib.table.csv2st()
- iolib.table.SimpleTable()
- SimpleTable.append()
- SimpleTable.as_csv()
- SimpleTable.as_html()
- SimpleTable.as_latex_tabular()
- SimpleTable.as_text()
- SimpleTable.clear()
- SimpleTable.copy()
- SimpleTable.count()
- SimpleTable.extend()
- SimpleTable.extend_right()
- SimpleTable.get_colwidths()
- SimpleTable.index()
- SimpleTable.insert()
- SimpleTable.insert_header_row()
- SimpleTable.insert_stubs()
- SimpleTable.label_cells()
- SimpleTable.pad()
- SimpleTable.pop()
- SimpleTable.remove()
- SimpleTable.reverse()
- SimpleTable.sort()
- StataReader.dataset()
- StataReader.file_format()
- StataReader.file_headers()
- StataReader.file_label()
- StataReader.file_timestamp()
- StataReader.variables()
- StataWriter.write_file()
- Summary.add_array()
- Summary.add_base()
- Summary.add_df()
- Summary.add_dict()
- Summary.add_extra_txt()
- Summary.add_table_2cols()
- Summary.add_table_params()
- Summary.add_text()
- Summary.add_title()
- Summary.as_csv()
- Summary.as_html()
- Summary.as_html()
- Summary.as_latex()
- Summary.as_latex()
- Summary.as_text()
- Summary.as_text()
Linear Mixed Effects Models
- MixedLM.fit()
- MixedLM.fit_regularized()
- MixedLM.from_formula()
- MixedLM.get_fe_params()
- MixedLM.get_scale()
- MixedLM.group_list()
- MixedLM.hessian()
- MixedLM.information()
- MixedLM.initialize()
- MixedLM.loglike()
- MixedLM.predict()
- MixedLM.score()
- MixedLM.score_full()
- MixedLM.score_sqrt()
- MixedLMResults.aic()
- MixedLMResults.bic()
- MixedLMResults.bootstrap()
- MixedLMResults.bse()
- MixedLMResults.bsejac()
- MixedLMResults.bsejhj()
- MixedLMResults.bse_fe()
- MixedLMResults.bse_re()
- MixedLMResults.conf_int()
- MixedLMResults.covjac()
- MixedLMResults.covjhj()
- MixedLMResults.cov_params()
- MixedLMResults.df_modelwc()
- MixedLMResults.fittedvalues()
- MixedLMResults.f_test()
- MixedLMResults.get_nlfun()
- MixedLMResults.hessv()
- MixedLMResults.initialize()
- MixedLMResults.llf()
- MixedLMResults.load()
- MixedLMResults.normalized_cov_params()
- MixedLMResults.predict()
- MixedLMResults.profile_re()
- MixedLMResults.pvalues()
- MixedLMResults.random_effects()
- MixedLMResults.random_effects_cov()
- MixedLMResults.remove_data()
- MixedLMResults.resid()
- MixedLMResults.save()
- MixedLMResults.score_obsv()
- MixedLMResults.summary()
- MixedLMResults.tvalues()
- MixedLMResults.t_test()
- MixedLMResults.t_test_pairwise()
- MixedLMResults.wald_test()
- MixedLMResults.wald_test_terms()
- regression.mixed_linear_model.MixedLM()
- regression.mixed_linear_model.MixedLMResults()
Linear Regression
- GLS.fit()
- GLS.fit_regularized()
- GLS.from_formula()
- GLS.get_distribution()
- GLS.hessian()
- GLS.hessian_factor()
- GLS.information()
- GLS.initialize()
- GLS.loglike()
- GLS.predict()
- GLS.score()
- GLS.whiten()
- GLSAR.fit()
- GLSAR.fit_regularized()
- GLSAR.from_formula()
- GLSAR.get_distribution()
- GLSAR.hessian()
- GLSAR.hessian_factor()
- GLSAR.information()
- GLSAR.initialize()
- GLSAR.iterative_fit()
- GLSAR.loglike()
- GLSAR.predict()
- GLSAR.score()
- GLSAR.whiten()
- OLS.fit()
- OLS.fit_regularized()
- OLS.from_formula()
- OLS.get_distribution()
- OLS.hessian()
- OLS.hessian_factor()
- OLS.information()
- OLS.initialize()
- OLS.loglike()
- OLS.predict()
- OLS.score()
- OLS.whiten()
- OLSResults.aic()
- OLSResults.bic()
- OLSResults.bse()
- OLSResults.centered_tss()
- OLSResults.compare_f_test()
- OLSResults.compare_lm_test()
- OLSResults.compare_lr_test()
- OLSResults.condition_number()
- OLSResults.conf_int()
- OLSResults.conf_int_el()
- OLSResults.cov_HC0()
- OLSResults.cov_HC1()
- OLSResults.cov_HC2()
- OLSResults.cov_HC3()
- OLSResults.cov_params()
- OLSResults.eigenvals()
- OLSResults.el_test()
- OLSResults.ess()
- OLSResults.fittedvalues()
- OLSResults.fvalue()
- OLSResults.f_pvalue()
- OLSResults.f_test()
- OLSResults.get_influence()
- OLSResults.get_prediction()
- OLSResults.get_robustcov_results()
- OLSResults.HC0_se()
- OLSResults.HC1_se()
- OLSResults.HC2_se()
- OLSResults.HC3_se()
- OLSResults.initialize()
- OLSResults.llf()
- OLSResults.load()
- OLSResults.mse_model()
- OLSResults.mse_resid()
- OLSResults.mse_total()
- OLSResults.nobs()
- OLSResults.normalized_cov_params()
- OLSResults.outlier_test()
- OLSResults.predict()
- OLSResults.pvalues()
- OLSResults.remove_data()
- OLSResults.resid()
- OLSResults.resid_pearson()
- OLSResults.rsquared()
- OLSResults.rsquared_adj()
- OLSResults.save()
- OLSResults.scale()
- OLSResults.ssr()
- OLSResults.summary()
- OLSResults.summary2()
- OLSResults.tvalues()
- OLSResults.t_test()
- OLSResults.t_test_pairwise()
- OLSResults.uncentered_tss()
- OLSResults.wald_test()
- OLSResults.wald_test_terms()
- OLSResults.wresid()
- PredictionResults.conf_int()
- PredictionResults.summary_frame()
- QuantReg.fit()
- QuantReg.from_formula()
- QuantReg.get_distribution()
- QuantReg.hessian()
- QuantReg.information()
- QuantReg.initialize()
- QuantReg.loglike()
- QuantReg.predict()
- QuantReg.score()
- QuantReg.whiten()
- QuantRegResults.aic()
- QuantRegResults.bic()
- QuantRegResults.bse()
- QuantRegResults.centered_tss()
- QuantRegResults.compare_f_test()
- QuantRegResults.compare_lm_test()
- QuantRegResults.compare_lr_test()
- QuantRegResults.condition_number()
- QuantRegResults.conf_int()
- QuantRegResults.cov_HC0()
- QuantRegResults.cov_HC1()
- QuantRegResults.cov_HC2()
- QuantRegResults.cov_HC3()
- QuantRegResults.cov_params()
- QuantRegResults.eigenvals()
- QuantRegResults.ess()
- QuantRegResults.fittedvalues()
- QuantRegResults.fvalue()
- QuantRegResults.f_pvalue()
- QuantRegResults.f_test()
- QuantRegResults.get_prediction()
- QuantRegResults.get_robustcov_results()
- QuantRegResults.HC0_se()
- QuantRegResults.HC1_se()
- QuantRegResults.HC2_se()
- QuantRegResults.HC3_se()
- QuantRegResults.initialize()
- QuantRegResults.llf()
- QuantRegResults.load()
- QuantRegResults.mse()
- QuantRegResults.mse_model()
- QuantRegResults.mse_resid()
- QuantRegResults.mse_total()
- QuantRegResults.nobs()
- QuantRegResults.normalized_cov_params()
- QuantRegResults.predict()
- QuantRegResults.prsquared()
- QuantRegResults.pvalues()
- QuantRegResults.remove_data()
- QuantRegResults.resid()
- QuantRegResults.resid_pearson()
- QuantRegResults.rsquared()
- QuantRegResults.rsquared_adj()
- QuantRegResults.save()
- QuantRegResults.scale()
- QuantRegResults.ssr()
- QuantRegResults.summary()
- QuantRegResults.summary2()
- QuantRegResults.tvalues()
- QuantRegResults.t_test()
- QuantRegResults.t_test_pairwise()
- QuantRegResults.uncentered_tss()
- QuantRegResults.wald_test()
- QuantRegResults.wald_test_terms()
- QuantRegResults.wresid()
- RecursiveLS.filter()
- RecursiveLS.fit()
- RecursiveLS.from_formula()
- RecursiveLS.hessian()
- RecursiveLS.impulse_responses()
- RecursiveLS.information()
- RecursiveLS.initialize()
- RecursiveLS.initialize_approximate_diffuse()
- RecursiveLS.initialize_known()
- RecursiveLS.initialize_statespace()
- RecursiveLS.initialize_stationary()
- RecursiveLS.loglike()
- RecursiveLS.loglikeobs()
- RecursiveLS.observed_information_matrix()
- RecursiveLS.opg_information_matrix()
- RecursiveLS.predict()
- RecursiveLS.prepare_data()
- RecursiveLS.score()
- RecursiveLS.score_obs()
- RecursiveLS.set_conserve_memory()
- RecursiveLS.set_filter_method()
- RecursiveLS.set_inversion_method()
- RecursiveLS.set_smoother_output()
- RecursiveLS.set_stability_method()
- RecursiveLS.simulate()
- RecursiveLS.simulation_smoother()
- RecursiveLS.smooth()
- RecursiveLS.transform_jacobian()
- RecursiveLS.transform_params()
- RecursiveLS.untransform_params()
- RecursiveLS.update()
- RecursiveLSResults.aic()
- RecursiveLSResults.bic()
- RecursiveLSResults.bse()
- RecursiveLSResults.conf_int()
- RecursiveLSResults.cov_params()
- RecursiveLSResults.cov_params_approx()
- RecursiveLSResults.cov_params_oim()
- RecursiveLSResults.cov_params_opg()
- RecursiveLSResults.cov_params_robust()
- RecursiveLSResults.cov_params_robust_approx()
- RecursiveLSResults.cov_params_robust_oim()
- RecursiveLSResults.cusum()
- RecursiveLSResults.cusum_squares()
- RecursiveLSResults.fittedvalues()
- RecursiveLSResults.forecast()
- RecursiveLSResults.f_test()
- RecursiveLSResults.get_forecast()
- RecursiveLSResults.get_prediction()
- RecursiveLSResults.hqic()
- RecursiveLSResults.impulse_responses()
- RecursiveLSResults.info_criteria()
- RecursiveLSResults.initialize()
- RecursiveLSResults.llf()
- RecursiveLSResults.llf_obs()
- RecursiveLSResults.load()
- RecursiveLSResults.loglikelihood_burn()
- RecursiveLSResults.normalized_cov_params()
- RecursiveLSResults.plot_cusum()
- RecursiveLSResults.plot_cusum_squares()
- RecursiveLSResults.plot_diagnostics()
- RecursiveLSResults.plot_recursive_coefficient()
- RecursiveLSResults.predict()
- RecursiveLSResults.pvalues()
- RecursiveLSResults.remove_data()
- RecursiveLSResults.resid()
- RecursiveLSResults.resid_recursive()
- RecursiveLSResults.save()
- RecursiveLSResults.simulate()
- RecursiveLSResults.summary()
- RecursiveLSResults.test_heteroskedasticity()
- RecursiveLSResults.test_normality()
- RecursiveLSResults.test_serial_correlation()
- RecursiveLSResults.tvalues()
- RecursiveLSResults.t_test()
- RecursiveLSResults.t_test_pairwise()
- RecursiveLSResults.wald_test()
- RecursiveLSResults.wald_test_terms()
- RecursiveLSResults.zvalues()
- regression.linear_model.GLS()
- regression.linear_model.GLSAR()
- regression.linear_model.OLS()
- regression.linear_model.OLSResults()
- regression.linear_model.PredictionResults()
- regression.linear_model.RegressionResults()
- regression.linear_model.WLS()
- regression.linear_model.yule_walker()
- regression.quantile_regression.QuantReg()
- regression.quantile_regression.QuantRegResults()
- regression.recursive_ls.RecursiveLS()
- regression.recursive_ls.RecursiveLSResults()
- RegressionResults.aic()
- RegressionResults.bic()
- RegressionResults.bse()
- RegressionResults.centered_tss()
- RegressionResults.compare_f_test()
- RegressionResults.compare_lm_test()
- RegressionResults.compare_lr_test()
- RegressionResults.condition_number()
- RegressionResults.conf_int()
- RegressionResults.cov_HC0()
- RegressionResults.cov_HC1()
- RegressionResults.cov_HC2()
- RegressionResults.cov_HC3()
- RegressionResults.cov_params()
- RegressionResults.eigenvals()
- RegressionResults.ess()
- RegressionResults.fittedvalues()
- RegressionResults.fvalue()
- RegressionResults.f_pvalue()
- RegressionResults.f_test()
- RegressionResults.get_prediction()
- RegressionResults.get_robustcov_results()
- RegressionResults.HC0_se()
- RegressionResults.HC1_se()
- RegressionResults.HC2_se()
- RegressionResults.HC3_se()
- RegressionResults.initialize()
- RegressionResults.llf()
- RegressionResults.load()
- RegressionResults.mse_model()
- RegressionResults.mse_resid()
- RegressionResults.mse_total()
- RegressionResults.nobs()
- RegressionResults.normalized_cov_params()
- RegressionResults.predict()
- RegressionResults.pvalues()
- RegressionResults.remove_data()
- RegressionResults.resid()
- RegressionResults.resid_pearson()
- RegressionResults.rsquared()
- RegressionResults.rsquared_adj()
- RegressionResults.save()
- RegressionResults.scale()
- RegressionResults.ssr()
- RegressionResults.summary()
- RegressionResults.summary2()
- RegressionResults.tvalues()
- RegressionResults.t_test()
- RegressionResults.t_test_pairwise()
- RegressionResults.uncentered_tss()
- RegressionResults.wald_test()
- RegressionResults.wald_test_terms()
- RegressionResults.wresid()
- WLS.fit()
- WLS.fit_regularized()
- WLS.from_formula()
- WLS.get_distribution()
- WLS.hessian()
- WLS.hessian_factor()
- WLS.information()
- WLS.initialize()
- WLS.loglike()
- WLS.predict()
- WLS.score()
- WLS.whiten()
Manual
- Manual: ANOVA
- Manual: Contingency tables
- Manual: Distributions
- Manual: Empirical Likelihood emplike
- Manual: endog, exog, what’s that?
- Manual: Fitting models using R-style formulas
- Manual: Frequently Asked Question
- Manual: Generalized Estimating Equations
- Manual: Generalized Linear Mixed Effects Models
- Manual: Generalized Linear Models
- Manual: Generalized Method of Moments gmm
- Manual: Getting started
- Manual: Graphics
- Manual: Import Paths and Structure
- Manual: Input-Output iolib
- Manual: Installation
- Manual: Linear Mixed Effects Models
- Manual: Linear Regression
- Manual: Methods for Survival and Duration Analysis
- Manual: Multiple Imputation with Chained Equations
- Manual: Multivariate Statistics multivariate
- Manual: Nonparametric Methods nonparametric
- Manual: Other Models miscmodels
- Manual: Patsy: Contrast Coding Systems for categorical variables
- Manual: Pitfalls
- Manual: Python Module Index
- Manual: Regression Diagnostics and Specification Tests
- Manual: Regression with Discrete Dependent Variable
- Manual: Robust Linear Models
- Manual: Sandbox
- Manual: Statistics stats
- Manual: Time Series Analysis by State Space Methods statespace
- Manual: Time Series analysis tsa
- Manual: Tools
- Manual: Vector Autoregressions tsa.vector_ar
- Manual: Weight Functions
Methods for Survival and Duration Analysis
- duration.hazard_regression.PHReg()
- duration.hazard_regression.PHRegResults()
- duration.survfunc.SurvfuncRight()
- PHReg.baseline_cumulative_hazard()
- PHReg.baseline_cumulative_hazard_function()
- PHReg.breslow_gradient()
- PHReg.breslow_hessian()
- PHReg.breslow_loglike()
- PHReg.efron_gradient()
- PHReg.efron_hessian()
- PHReg.efron_loglike()
- PHReg.fit()
- PHReg.fit_regularized()
- PHReg.from_formula()
- PHReg.get_distribution()
- PHReg.hessian()
- PHReg.information()
- PHReg.initialize()
- PHReg.loglike()
- PHReg.predict()
- PHReg.robust_covariance()
- PHReg.score()
- PHReg.score_residuals()
- PHReg.weighted_covariate_averages()
- PHRegResults.baseline_cumulative_hazard()
- PHRegResults.baseline_cumulative_hazard_function()
- PHRegResults.bse()
- PHRegResults.conf_int()
- PHRegResults.cov_params()
- PHRegResults.f_test()
- PHRegResults.get_distribution()
- PHRegResults.initialize()
- PHRegResults.llf()
- PHRegResults.load()
- PHRegResults.martingale_residuals()
- PHRegResults.normalized_cov_params()
- PHRegResults.predict()
- PHRegResults.pvalues()
- PHRegResults.remove_data()
- PHRegResults.save()
- PHRegResults.schoenfeld_residuals()
- PHRegResults.score_residuals()
- PHRegResults.standard_errors()
- PHRegResults.summary()
- PHRegResults.tvalues()
- PHRegResults.t_test()
- PHRegResults.t_test_pairwise()
- PHRegResults.wald_test()
- PHRegResults.wald_test_terms()
- PHRegResults.weighted_covariate_averages()
- SurvfuncRight.plot()
- SurvfuncRight.quantile()
- SurvfuncRight.quantile_ci()
- SurvfuncRight.simultaneous_cb()
- SurvfuncRight.summary()
Multiple Imputation with Chained Equations
- imputation.mice.MICE()
- imputation.mice.MICEData()
- MICE.combine()
- MICE.fit()
- MICE.next_sample()
- MICEData.get_fitting_data()
- MICEData.get_split_data()
- MICEData.impute()
- MICEData.impute_pmm()
- MICEData.next_sample()
- MICEData.perturb_params()
- MICEData.plot_bivariate()
- MICEData.plot_fit_obs()
- MICEData.plot_imputed_hist()
- MICEData.plot_missing_pattern()
- MICEData.set_imputer()
- MICEData.update()
- MICEData.update_all()
Multivariate Statistics
- CanCorr.corr_test()
- CanCorr.fit()
- CanCorr.from_formula()
- CanCorr.predict()
- Factor.fit()
- Factor.from_formula()
- Factor.loglike()
- Factor.predict()
- Factor.score()
- FactorResults.factor_score_params()
- FactorResults.factor_scoring()
- FactorResults.fitted_cov()
- FactorResults.get_loadings_frame()
- FactorResults.load_stderr()
- FactorResults.plot_loadings()
- FactorResults.plot_scree()
- FactorResults.rotate()
- FactorResults.summary()
- FactorResults.uniq_stderr()
- MANOVA.fit()
- MANOVA.from_formula()
- MANOVA.mv_test()
- MANOVA.predict()
- multivariate.cancorr.CanCorr()
- multivariate.factor.Factor()
- multivariate.factor.FactorResults()
- multivariate.factor_rotation.procrustes()
- multivariate.factor_rotation.promax()
- multivariate.factor_rotation.rotate_factors()
- multivariate.factor_rotation.target_rotation()
- multivariate.manova.MANOVA()
- multivariate.multivariate_ols.MultivariateTestResults()
- multivariate.multivariate_ols._MultivariateOLS()
- multivariate.multivariate_ols._MultivariateOLSResults()
- multivariate.pca.PCA()
- MultivariateTestResults.summary()
- PCA.plot_rsquare()
- PCA.plot_scree()
- PCA.project()
- _MultivariateOLS.fit()
- _MultivariateOLS.from_formula()
- _MultivariateOLS.predict()
- _MultivariateOLSResults.mv_test()
- _MultivariateOLSResults.summary()
Nonparametric Methods
- KDEMultivariate.cdf()
- KDEMultivariate.imse()
- KDEMultivariate.loo_likelihood()
- KDEMultivariate.pdf()
- KDEMultivariateConditional.cdf()
- KDEMultivariateConditional.imse()
- KDEMultivariateConditional.loo_likelihood()
- KDEMultivariateConditional.pdf()
- KDEUnivariate.cdf()
- KDEUnivariate.cumhazard()
- KDEUnivariate.entropy()
- KDEUnivariate.evaluate()
- KDEUnivariate.fit()
- KDEUnivariate.icdf()
- KDEUnivariate.sf()
- KernelCensoredReg.aic_hurvich()
- KernelCensoredReg.censored()
- KernelCensoredReg.cv_loo()
- KernelCensoredReg.fit()
- KernelCensoredReg.loo_likelihood()
- KernelCensoredReg.r_squared()
- KernelCensoredReg.sig_test()
- KernelReg.aic_hurvich()
- KernelReg.cv_loo()
- KernelReg.fit()
- KernelReg.loo_likelihood()
- KernelReg.r_squared()
- KernelReg.sig_test()
- nonparametric.bandwidths.bw_scott()
- nonparametric.bandwidths.bw_silverman()
- nonparametric.bandwidths.select_bandwidth()
- nonparametric.kde.KDEUnivariate()
- nonparametric.kernel_density.EstimatorSettings()
- nonparametric.kernel_density.KDEMultivariate()
- nonparametric.kernel_density.KDEMultivariateConditional()
- nonparametric.kernel_regression.KernelCensoredReg()
- nonparametric.kernel_regression.KernelReg()
- nonparametric.smoothers_lowess.lowess()
Other Models
- miscmodels.count.PoissonGMLE()
- miscmodels.count.PoissonOffsetGMLE()
- miscmodels.count.PoissonZiGMLE()
- miscmodels.tmodel.TLinearModel()
- PoissonGMLE.expandparams()
- PoissonGMLE.fit()
- PoissonGMLE.from_formula()
- PoissonGMLE.hessian()
- PoissonGMLE.hessian_factor()
- PoissonGMLE.information()
- PoissonGMLE.initialize()
- PoissonGMLE.loglike()
- PoissonGMLE.loglikeobs()
- PoissonGMLE.nloglike()
- PoissonGMLE.nloglikeobs()
- PoissonGMLE.predict()
- PoissonGMLE.predict_distribution()
- PoissonGMLE.reduceparams()
- PoissonGMLE.score()
- PoissonGMLE.score_obs()
- PoissonOffsetGMLE.expandparams()
- PoissonOffsetGMLE.fit()
- PoissonOffsetGMLE.from_formula()
- PoissonOffsetGMLE.hessian()
- PoissonOffsetGMLE.hessian_factor()
- PoissonOffsetGMLE.information()
- PoissonOffsetGMLE.initialize()
- PoissonOffsetGMLE.loglike()
- PoissonOffsetGMLE.loglikeobs()
- PoissonOffsetGMLE.nloglike()
- PoissonOffsetGMLE.nloglikeobs()
- PoissonOffsetGMLE.predict()
- PoissonOffsetGMLE.reduceparams()
- PoissonOffsetGMLE.score()
- PoissonOffsetGMLE.score_obs()
- PoissonZiGMLE.expandparams()
- PoissonZiGMLE.fit()
- PoissonZiGMLE.from_formula()
- PoissonZiGMLE.hessian()
- PoissonZiGMLE.hessian_factor()
- PoissonZiGMLE.information()
- PoissonZiGMLE.initialize()
- PoissonZiGMLE.loglike()
- PoissonZiGMLE.loglikeobs()
- PoissonZiGMLE.nloglike()
- PoissonZiGMLE.nloglikeobs()
- PoissonZiGMLE.predict()
- PoissonZiGMLE.reduceparams()
- PoissonZiGMLE.score()
- PoissonZiGMLE.score_obs()
- TLinearModel.expandparams()
- TLinearModel.fit()
- TLinearModel.from_formula()
- TLinearModel.hessian()
- TLinearModel.hessian_factor()
- TLinearModel.information()
- TLinearModel.initialize()
- TLinearModel.loglike()
- TLinearModel.loglikeobs()
- TLinearModel.nloglike()
- TLinearModel.nloglikeobs()
- TLinearModel.predict()
- TLinearModel.reduceparams()
- TLinearModel.score()
- TLinearModel.score_obs()
Regression with Discrete Dependent Variable
- BinaryModel.cdf()
- BinaryModel.cov_params_func_l1()
- BinaryModel.fit()
- BinaryModel.fit_regularized()
- BinaryModel.from_formula()
- BinaryModel.hessian()
- BinaryModel.information()
- BinaryModel.initialize()
- BinaryModel.loglike()
- BinaryModel.pdf()
- BinaryModel.predict()
- BinaryModel.score()
- BinaryResults.aic()
- BinaryResults.bic()
- BinaryResults.bse()
- BinaryResults.conf_int()
- BinaryResults.cov_params()
- BinaryResults.fittedvalues()
- BinaryResults.f_test()
- BinaryResults.get_margeff()
- BinaryResults.initialize()
- BinaryResults.llf()
- BinaryResults.llnull()
- BinaryResults.llr()
- BinaryResults.llr_pvalue()
- BinaryResults.load()
- BinaryResults.normalized_cov_params()
- BinaryResults.predict()
- BinaryResults.pred_table()
- BinaryResults.prsquared()
- BinaryResults.pvalues()
- BinaryResults.remove_data()
- BinaryResults.resid_dev()
- BinaryResults.resid_pearson()
- BinaryResults.resid_response()
- BinaryResults.save()
- BinaryResults.set_null_options()
- BinaryResults.summary()
- BinaryResults.summary2()
- BinaryResults.tvalues()
- BinaryResults.t_test()
- BinaryResults.t_test_pairwise()
- BinaryResults.wald_test()
- BinaryResults.wald_test_terms()
- CountModel.cdf()
- CountModel.cov_params_func_l1()
- CountModel.fit()
- CountModel.fit_regularized()
- CountModel.from_formula()
- CountModel.hessian()
- CountModel.information()
- CountModel.initialize()
- CountModel.loglike()
- CountModel.pdf()
- CountModel.predict()
- CountModel.score()
- CountResults.aic()
- CountResults.bic()
- CountResults.bse()
- CountResults.conf_int()
- CountResults.cov_params()
- CountResults.fittedvalues()
- CountResults.f_test()
- CountResults.get_margeff()
- CountResults.initialize()
- CountResults.llf()
- CountResults.llnull()
- CountResults.llr()
- CountResults.llr_pvalue()
- CountResults.load()
- CountResults.normalized_cov_params()
- CountResults.predict()
- CountResults.prsquared()
- CountResults.pvalues()
- CountResults.remove_data()
- CountResults.resid()
- CountResults.save()
- CountResults.set_null_options()
- CountResults.summary()
- CountResults.summary2()
- CountResults.tvalues()
- CountResults.t_test()
- CountResults.t_test_pairwise()
- CountResults.wald_test()
- CountResults.wald_test_terms()
- discrete.count_model.GenericZeroInflated()
- discrete.count_model.ZeroInflatedGeneralizedPoisson()
- discrete.count_model.ZeroInflatedGeneralizedPoissonResults()
- discrete.count_model.ZeroInflatedNegativeBinomialP()
- discrete.count_model.ZeroInflatedNegativeBinomialResults()
- discrete.count_model.ZeroInflatedPoisson()
- discrete.count_model.ZeroInflatedPoissonResults()
- discrete.discrete_model.BinaryModel()
- discrete.discrete_model.BinaryResults()
- discrete.discrete_model.CountModel()
- discrete.discrete_model.CountResults()
- discrete.discrete_model.DiscreteModel()
- discrete.discrete_model.DiscreteResults()
- discrete.discrete_model.GeneralizedPoisson()
- discrete.discrete_model.GeneralizedPoissonResults()
- discrete.discrete_model.Logit()
- discrete.discrete_model.LogitResults()
- discrete.discrete_model.MNLogit()
- discrete.discrete_model.MultinomialModel()
- discrete.discrete_model.MultinomialResults()
- discrete.discrete_model.NegativeBinomial()
- discrete.discrete_model.NegativeBinomialP()
- discrete.discrete_model.NegativeBinomialResults()
- discrete.discrete_model.Poisson()
- discrete.discrete_model.Probit()
- discrete.discrete_model.ProbitResults()
- DiscreteModel.cdf()
- DiscreteModel.cov_params_func_l1()
- DiscreteModel.fit()
- DiscreteModel.fit_regularized()
- DiscreteModel.from_formula()
- DiscreteModel.hessian()
- DiscreteModel.information()
- DiscreteModel.initialize()
- DiscreteModel.loglike()
- DiscreteModel.pdf()
- DiscreteModel.predict()
- DiscreteModel.score()
- DiscreteResults.aic()
- DiscreteResults.bic()
- DiscreteResults.bse()
- DiscreteResults.conf_int()
- DiscreteResults.cov_params()
- DiscreteResults.fittedvalues()
- DiscreteResults.f_test()
- DiscreteResults.get_margeff()
- DiscreteResults.initialize()
- DiscreteResults.llf()
- DiscreteResults.llnull()
- DiscreteResults.llr()
- DiscreteResults.llr_pvalue()
- DiscreteResults.load()
- DiscreteResults.normalized_cov_params()
- DiscreteResults.predict()
- DiscreteResults.prsquared()
- DiscreteResults.pvalues()
- DiscreteResults.remove_data()
- DiscreteResults.save()
- DiscreteResults.set_null_options()
- DiscreteResults.summary()
- DiscreteResults.summary2()
- DiscreteResults.tvalues()
- DiscreteResults.t_test()
- DiscreteResults.t_test_pairwise()
- DiscreteResults.wald_test()
- DiscreteResults.wald_test_terms()
- GeneralizedPoisson.cdf()
- GeneralizedPoisson.cov_params_func_l1()
- GeneralizedPoisson.fit()
- GeneralizedPoisson.fit_regularized()
- GeneralizedPoisson.from_formula()
- GeneralizedPoisson.hessian()
- GeneralizedPoisson.information()
- GeneralizedPoisson.initialize()
- GeneralizedPoisson.loglike()
- GeneralizedPoisson.loglikeobs()
- GeneralizedPoisson.pdf()
- GeneralizedPoisson.predict()
- GeneralizedPoisson.score()
- GeneralizedPoisson.score_obs()
- GeneralizedPoissonResults.aic()
- GeneralizedPoissonResults.bic()
- GeneralizedPoissonResults.bse()
- GeneralizedPoissonResults.conf_int()
- GeneralizedPoissonResults.cov_params()
- GeneralizedPoissonResults.fittedvalues()
- GeneralizedPoissonResults.f_test()
- GeneralizedPoissonResults.get_margeff()
- GeneralizedPoissonResults.initialize()
- GeneralizedPoissonResults.llf()
- GeneralizedPoissonResults.llnull()
- GeneralizedPoissonResults.llr()
- GeneralizedPoissonResults.llr_pvalue()
- GeneralizedPoissonResults.lnalpha()
- GeneralizedPoissonResults.lnalpha_std_err()
- GeneralizedPoissonResults.load()
- GeneralizedPoissonResults.normalized_cov_params()
- GeneralizedPoissonResults.predict()
- GeneralizedPoissonResults.prsquared()
- GeneralizedPoissonResults.pvalues()
- GeneralizedPoissonResults.remove_data()
- GeneralizedPoissonResults.resid()
- GeneralizedPoissonResults.save()
- GeneralizedPoissonResults.set_null_options()
- GeneralizedPoissonResults.summary()
- GeneralizedPoissonResults.summary2()
- GeneralizedPoissonResults.tvalues()
- GeneralizedPoissonResults.t_test()
- GeneralizedPoissonResults.t_test_pairwise()
- GeneralizedPoissonResults.wald_test()
- GeneralizedPoissonResults.wald_test_terms()
- GenericZeroInflated.cdf()
- GenericZeroInflated.cov_params_func_l1()
- GenericZeroInflated.fit()
- GenericZeroInflated.fit_regularized()
- GenericZeroInflated.from_formula()
- GenericZeroInflated.hessian()
- GenericZeroInflated.information()
- GenericZeroInflated.initialize()
- GenericZeroInflated.loglike()
- GenericZeroInflated.loglikeobs()
- GenericZeroInflated.pdf()
- GenericZeroInflated.predict()
- GenericZeroInflated.score()
- GenericZeroInflated.score_obs()
- Logit.cdf()
- Logit.cov_params_func_l1()
- Logit.fit()
- Logit.fit_regularized()
- Logit.from_formula()
- Logit.hessian()
- Logit.information()
- Logit.initialize()
- Logit.loglike()
- Logit.loglikeobs()
- Logit.pdf()
- Logit.predict()
- Logit.score()
- Logit.score_obs()
- LogitResults.aic()
- LogitResults.bic()
- LogitResults.bse()
- LogitResults.conf_int()
- LogitResults.cov_params()
- LogitResults.fittedvalues()
- LogitResults.f_test()
- LogitResults.get_margeff()
- LogitResults.initialize()
- LogitResults.llf()
- LogitResults.llnull()
- LogitResults.llr()
- LogitResults.llr_pvalue()
- LogitResults.load()
- LogitResults.normalized_cov_params()
- LogitResults.predict()
- LogitResults.pred_table()
- LogitResults.prsquared()
- LogitResults.pvalues()
- LogitResults.remove_data()
- LogitResults.resid_dev()
- LogitResults.resid_generalized()
- LogitResults.resid_pearson()
- LogitResults.resid_response()
- LogitResults.save()
- LogitResults.set_null_options()
- LogitResults.summary()
- LogitResults.summary2()
- LogitResults.tvalues()
- LogitResults.t_test()
- LogitResults.t_test_pairwise()
- LogitResults.wald_test()
- LogitResults.wald_test_terms()
- MNLogit.cdf()
- MNLogit.cov_params_func_l1()
- MNLogit.fit()
- MNLogit.fit_regularized()
- MNLogit.from_formula()
- MNLogit.hessian()
- MNLogit.information()
- MNLogit.initialize()
- MNLogit.loglike()
- MNLogit.loglikeobs()
- MNLogit.loglike_and_score()
- MNLogit.pdf()
- MNLogit.predict()
- MNLogit.score()
- MNLogit.score_obs()
- MultinomialModel.cdf()
- MultinomialModel.cov_params_func_l1()
- MultinomialModel.fit()
- MultinomialModel.fit_regularized()
- MultinomialModel.from_formula()
- MultinomialModel.hessian()
- MultinomialModel.information()
- MultinomialModel.initialize()
- MultinomialModel.loglike()
- MultinomialModel.pdf()
- MultinomialModel.predict()
- MultinomialModel.score()
- MultinomialResults.aic()
- MultinomialResults.bic()
- MultinomialResults.bse()
- MultinomialResults.conf_int()
- MultinomialResults.cov_params()
- MultinomialResults.fittedvalues()
- MultinomialResults.f_test()
- MultinomialResults.get_margeff()
- MultinomialResults.initialize()
- MultinomialResults.llf()
- MultinomialResults.llnull()
- MultinomialResults.llr()
- MultinomialResults.llr_pvalue()
- MultinomialResults.load()
- MultinomialResults.margeff()
- MultinomialResults.normalized_cov_params()
- MultinomialResults.predict()
- MultinomialResults.pred_table()
- MultinomialResults.prsquared()
- MultinomialResults.pvalues()
- MultinomialResults.remove_data()
- MultinomialResults.resid_misclassified()
- MultinomialResults.save()
- MultinomialResults.set_null_options()
- MultinomialResults.summary()
- MultinomialResults.summary2()
- MultinomialResults.tvalues()
- MultinomialResults.t_test()
- MultinomialResults.t_test_pairwise()
- MultinomialResults.wald_test()
- MultinomialResults.wald_test_terms()
- NegativeBinomial.cdf()
- NegativeBinomial.cov_params_func_l1()
- NegativeBinomial.fit()
- NegativeBinomial.fit_regularized()
- NegativeBinomial.from_formula()
- NegativeBinomial.hessian()
- NegativeBinomial.information()
- NegativeBinomial.initialize()
- NegativeBinomial.loglike()
- NegativeBinomial.pdf()
- NegativeBinomial.predict()
- NegativeBinomial.score()
- NegativeBinomial.score_obs()
- NegativeBinomialP.cdf()
- NegativeBinomialP.convert_params()
- NegativeBinomialP.cov_params_func_l1()
- NegativeBinomialP.fit()
- NegativeBinomialP.fit_regularized()
- NegativeBinomialP.from_formula()
- NegativeBinomialP.hessian()
- NegativeBinomialP.information()
- NegativeBinomialP.initialize()
- NegativeBinomialP.loglike()
- NegativeBinomialP.loglikeobs()
- NegativeBinomialP.pdf()
- NegativeBinomialP.predict()
- NegativeBinomialP.score()
- NegativeBinomialP.score_obs()
- NegativeBinomialResults.aic()
- NegativeBinomialResults.bic()
- NegativeBinomialResults.bse()
- NegativeBinomialResults.conf_int()
- NegativeBinomialResults.cov_params()
- NegativeBinomialResults.fittedvalues()
- NegativeBinomialResults.f_test()
- NegativeBinomialResults.get_margeff()
- NegativeBinomialResults.initialize()
- NegativeBinomialResults.llf()
- NegativeBinomialResults.llnull()
- NegativeBinomialResults.llr()
- NegativeBinomialResults.llr_pvalue()
- NegativeBinomialResults.lnalpha()
- NegativeBinomialResults.lnalpha_std_err()
- NegativeBinomialResults.load()
- NegativeBinomialResults.normalized_cov_params()
- NegativeBinomialResults.predict()
- NegativeBinomialResults.prsquared()
- NegativeBinomialResults.pvalues()
- NegativeBinomialResults.remove_data()
- NegativeBinomialResults.resid()
- NegativeBinomialResults.save()
- NegativeBinomialResults.set_null_options()
- NegativeBinomialResults.summary()
- NegativeBinomialResults.summary2()
- NegativeBinomialResults.tvalues()
- NegativeBinomialResults.t_test()
- NegativeBinomialResults.t_test_pairwise()
- NegativeBinomialResults.wald_test()
- NegativeBinomialResults.wald_test_terms()
- Poisson.cdf()
- Poisson.cov_params_func_l1()
- Poisson.fit()
- Poisson.fit_constrained()
- Poisson.fit_regularized()
- Poisson.from_formula()
- Poisson.hessian()
- Poisson.information()
- Poisson.initialize()
- Poisson.loglike()
- Poisson.loglikeobs()
- Poisson.pdf()
- Poisson.predict()
- Poisson.score()
- Poisson.score_obs()
- Probit.cdf()
- Probit.cov_params_func_l1()
- Probit.fit()
- Probit.fit_regularized()
- Probit.from_formula()
- Probit.hessian()
- Probit.information()
- Probit.initialize()
- Probit.loglike()
- Probit.loglikeobs()
- Probit.pdf()
- Probit.predict()
- Probit.score()
- Probit.score_obs()
- ProbitResults.aic()
- ProbitResults.bic()
- ProbitResults.bse()
- ProbitResults.conf_int()
- ProbitResults.cov_params()
- ProbitResults.fittedvalues()
- ProbitResults.f_test()
- ProbitResults.get_margeff()
- ProbitResults.initialize()
- ProbitResults.llf()
- ProbitResults.llnull()
- ProbitResults.llr()
- ProbitResults.llr_pvalue()
- ProbitResults.load()
- ProbitResults.normalized_cov_params()
- ProbitResults.predict()
- ProbitResults.pred_table()
- ProbitResults.prsquared()
- ProbitResults.pvalues()
- ProbitResults.remove_data()
- ProbitResults.resid_dev()
- ProbitResults.resid_generalized()
- ProbitResults.resid_pearson()
- ProbitResults.resid_response()
- ProbitResults.save()
- ProbitResults.set_null_options()
- ProbitResults.summary()
- ProbitResults.summary2()
- ProbitResults.tvalues()
- ProbitResults.t_test()
- ProbitResults.t_test_pairwise()
- ProbitResults.wald_test()
- ProbitResults.wald_test_terms()
- ZeroInflatedGeneralizedPoisson.cdf()
- ZeroInflatedGeneralizedPoisson.cov_params_func_l1()
- ZeroInflatedGeneralizedPoisson.fit()
- ZeroInflatedGeneralizedPoisson.fit_regularized()
- ZeroInflatedGeneralizedPoisson.from_formula()
- ZeroInflatedGeneralizedPoisson.hessian()
- ZeroInflatedGeneralizedPoisson.information()
- ZeroInflatedGeneralizedPoisson.initialize()
- ZeroInflatedGeneralizedPoisson.loglike()
- ZeroInflatedGeneralizedPoisson.loglikeobs()
- ZeroInflatedGeneralizedPoisson.pdf()
- ZeroInflatedGeneralizedPoisson.predict()
- ZeroInflatedGeneralizedPoisson.score()
- ZeroInflatedGeneralizedPoisson.score_obs()
- ZeroInflatedGeneralizedPoissonResults.aic()
- ZeroInflatedGeneralizedPoissonResults.bic()
- ZeroInflatedGeneralizedPoissonResults.bse()
- ZeroInflatedGeneralizedPoissonResults.conf_int()
- ZeroInflatedGeneralizedPoissonResults.cov_params()
- ZeroInflatedGeneralizedPoissonResults.fittedvalues()
- ZeroInflatedGeneralizedPoissonResults.f_test()
- ZeroInflatedGeneralizedPoissonResults.get_margeff()
- ZeroInflatedGeneralizedPoissonResults.initialize()
- ZeroInflatedGeneralizedPoissonResults.llf()
- ZeroInflatedGeneralizedPoissonResults.llnull()
- ZeroInflatedGeneralizedPoissonResults.llr()
- ZeroInflatedGeneralizedPoissonResults.llr_pvalue()
- ZeroInflatedGeneralizedPoissonResults.load()
- ZeroInflatedGeneralizedPoissonResults.normalized_cov_params()
- ZeroInflatedGeneralizedPoissonResults.predict()
- ZeroInflatedGeneralizedPoissonResults.prsquared()
- ZeroInflatedGeneralizedPoissonResults.pvalues()
- ZeroInflatedGeneralizedPoissonResults.remove_data()
- ZeroInflatedGeneralizedPoissonResults.resid()
- ZeroInflatedGeneralizedPoissonResults.save()
- ZeroInflatedGeneralizedPoissonResults.set_null_options()
- ZeroInflatedGeneralizedPoissonResults.summary()
- ZeroInflatedGeneralizedPoissonResults.summary2()
- ZeroInflatedGeneralizedPoissonResults.tvalues()
- ZeroInflatedGeneralizedPoissonResults.t_test()
- ZeroInflatedGeneralizedPoissonResults.t_test_pairwise()
- ZeroInflatedGeneralizedPoissonResults.wald_test()
- ZeroInflatedGeneralizedPoissonResults.wald_test_terms()
- ZeroInflatedNegativeBinomialP.cdf()
- ZeroInflatedNegativeBinomialP.cov_params_func_l1()
- ZeroInflatedNegativeBinomialP.fit()
- ZeroInflatedNegativeBinomialP.fit_regularized()
- ZeroInflatedNegativeBinomialP.from_formula()
- ZeroInflatedNegativeBinomialP.hessian()
- ZeroInflatedNegativeBinomialP.information()
- ZeroInflatedNegativeBinomialP.initialize()
- ZeroInflatedNegativeBinomialP.loglike()
- ZeroInflatedNegativeBinomialP.loglikeobs()
- ZeroInflatedNegativeBinomialP.pdf()
- ZeroInflatedNegativeBinomialP.predict()
- ZeroInflatedNegativeBinomialP.score()
- ZeroInflatedNegativeBinomialP.score_obs()
- ZeroInflatedNegativeBinomialResults.aic()
- ZeroInflatedNegativeBinomialResults.bic()
- ZeroInflatedNegativeBinomialResults.bse()
- ZeroInflatedNegativeBinomialResults.conf_int()
- ZeroInflatedNegativeBinomialResults.cov_params()
- ZeroInflatedNegativeBinomialResults.fittedvalues()
- ZeroInflatedNegativeBinomialResults.f_test()
- ZeroInflatedNegativeBinomialResults.get_margeff()
- ZeroInflatedNegativeBinomialResults.initialize()
- ZeroInflatedNegativeBinomialResults.llf()
- ZeroInflatedNegativeBinomialResults.llnull()
- ZeroInflatedNegativeBinomialResults.llr()
- ZeroInflatedNegativeBinomialResults.llr_pvalue()
- ZeroInflatedNegativeBinomialResults.load()
- ZeroInflatedNegativeBinomialResults.normalized_cov_params()
- ZeroInflatedNegativeBinomialResults.predict()
- ZeroInflatedNegativeBinomialResults.prsquared()
- ZeroInflatedNegativeBinomialResults.pvalues()
- ZeroInflatedNegativeBinomialResults.remove_data()
- ZeroInflatedNegativeBinomialResults.resid()
- ZeroInflatedNegativeBinomialResults.save()
- ZeroInflatedNegativeBinomialResults.set_null_options()
- ZeroInflatedNegativeBinomialResults.summary()
- ZeroInflatedNegativeBinomialResults.summary2()
- ZeroInflatedNegativeBinomialResults.tvalues()
- ZeroInflatedNegativeBinomialResults.t_test()
- ZeroInflatedNegativeBinomialResults.t_test_pairwise()
- ZeroInflatedNegativeBinomialResults.wald_test()
- ZeroInflatedNegativeBinomialResults.wald_test_terms()
- ZeroInflatedPoisson.cdf()
- ZeroInflatedPoisson.cov_params_func_l1()
- ZeroInflatedPoisson.fit()
- ZeroInflatedPoisson.fit_regularized()
- ZeroInflatedPoisson.from_formula()
- ZeroInflatedPoisson.hessian()
- ZeroInflatedPoisson.information()
- ZeroInflatedPoisson.initialize()
- ZeroInflatedPoisson.loglike()
- ZeroInflatedPoisson.loglikeobs()
- ZeroInflatedPoisson.pdf()
- ZeroInflatedPoisson.predict()
- ZeroInflatedPoisson.score()
- ZeroInflatedPoisson.score_obs()
- ZeroInflatedPoissonResults.aic()
- ZeroInflatedPoissonResults.bic()
- ZeroInflatedPoissonResults.bse()
- ZeroInflatedPoissonResults.conf_int()
- ZeroInflatedPoissonResults.cov_params()
- ZeroInflatedPoissonResults.fittedvalues()
- ZeroInflatedPoissonResults.f_test()
- ZeroInflatedPoissonResults.get_margeff()
- ZeroInflatedPoissonResults.initialize()
- ZeroInflatedPoissonResults.llf()
- ZeroInflatedPoissonResults.llnull()
- ZeroInflatedPoissonResults.llr()
- ZeroInflatedPoissonResults.llr_pvalue()
- ZeroInflatedPoissonResults.load()
- ZeroInflatedPoissonResults.normalized_cov_params()
- ZeroInflatedPoissonResults.predict()
- ZeroInflatedPoissonResults.prsquared()
- ZeroInflatedPoissonResults.pvalues()
- ZeroInflatedPoissonResults.remove_data()
- ZeroInflatedPoissonResults.resid()
- ZeroInflatedPoissonResults.save()
- ZeroInflatedPoissonResults.set_null_options()
- ZeroInflatedPoissonResults.summary()
- ZeroInflatedPoissonResults.summary2()
- ZeroInflatedPoissonResults.tvalues()
- ZeroInflatedPoissonResults.t_test()
- ZeroInflatedPoissonResults.t_test_pairwise()
- ZeroInflatedPoissonResults.wald_test()
- ZeroInflatedPoissonResults.wald_test_terms()
Robust Linear Models
- AndrewWave.psi()
- AndrewWave.psi_deriv()
- AndrewWave.rho()
- AndrewWave.weights()
- Hampel.psi()
- Hampel.psi_deriv()
- Hampel.rho()
- Hampel.weights()
- HuberT.psi()
- HuberT.psi_deriv()
- HuberT.rho()
- HuberT.weights()
- LeastSquares.psi()
- LeastSquares.psi_deriv()
- LeastSquares.rho()
- LeastSquares.weights()
- RamsayE.psi()
- RamsayE.psi_deriv()
- RamsayE.rho()
- RamsayE.weights()
- RLM.deviance()
- RLM.fit()
- RLM.from_formula()
- RLM.hessian()
- RLM.information()
- RLM.initialize()
- RLM.loglike()
- RLM.predict()
- RLM.score()
- RLMResults.bcov_scaled()
- RLMResults.bcov_unscaled()
- RLMResults.bse()
- RLMResults.chisq()
- RLMResults.conf_int()
- RLMResults.cov_params()
- RLMResults.fittedvalues()
- RLMResults.f_test()
- RLMResults.initialize()
- RLMResults.llf()
- RLMResults.load()
- RLMResults.normalized_cov_params()
- RLMResults.predict()
- RLMResults.pvalues()
- RLMResults.remove_data()
- RLMResults.resid()
- RLMResults.save()
- RLMResults.sresid()
- RLMResults.summary()
- RLMResults.summary2()
- RLMResults.tvalues()
- RLMResults.t_test()
- RLMResults.t_test_pairwise()
- RLMResults.wald_test()
- RLMResults.wald_test_terms()
- RLMResults.weights()
- robust.norms.AndrewWave()
- robust.norms.estimate_location()
- robust.norms.Hampel()
- robust.norms.HuberT()
- robust.norms.LeastSquares
- robust.norms.RamsayE()
- robust.norms.RobustNorm
- robust.norms.TrimmedMean()
- robust.norms.TukeyBiweight()
- robust.robust_linear_model.RLM()
- robust.robust_linear_model.RLMResults()
- robust.scale.Huber()
- robust.scale.HuberScale()
- robust.scale.hubers_scale
- robust.scale.mad()
- RobustNorm.psi()
- RobustNorm.psi_deriv()
- RobustNorm.rho()
- RobustNorm.weights()
- TrimmedMean.psi()
- TrimmedMean.psi_deriv()
- TrimmedMean.rho()
- TrimmedMean.weights()
- TukeyBiweight.psi()
- TukeyBiweight.psi_deriv()
- TukeyBiweight.rho()
- TukeyBiweight.weights()
Sandbox
- sandbox.descstats.descstats()
- sandbox.descstats.sign_test()
- sandbox.regression.anova_nistcertified.anova_ols()
- sandbox.regression.anova_nistcertified.anova_oneway()
- sandbox.regression.try_catdata.cat2dummy()
- sandbox.regression.try_catdata.convertlabels()
- sandbox.regression.try_catdata.groupsstats_1d()
- sandbox.regression.try_catdata.groupsstats_dummy()
- sandbox.regression.try_catdata.groupstatsbin()
- sandbox.regression.try_catdata.labelmeanfilter()
- sandbox.regression.try_catdata.labelmeanfilter_nd()
- sandbox.regression.try_catdata.labelmeanfilter_str()
- sandbox.regression.try_ols_anova.data2dummy()
- sandbox.regression.try_ols_anova.data2groupcont()
- sandbox.regression.try_ols_anova.data2proddummy()
- sandbox.regression.try_ols_anova.dropname()
- sandbox.regression.try_ols_anova.form2design()
- sandbox.sysreg.Sem2SLS()
- sandbox.sysreg.SUR()
- sandbox.tsa.movstat.movmean()
- sandbox.tsa.movstat.movmoment()
- sandbox.tsa.movstat.movorder()
- sandbox.tsa.movstat.movvar()
- Sem2SLS.fit()
- Sem2SLS.whiten()
- SUR.fit()
- SUR.initialize()
- SUR.predict()
- SUR.whiten()
Statistics
- CompareCox.run()
- CompareJ.run()
- CompareMeans.dof_satt()
- CompareMeans.from_data()
- CompareMeans.std_meandiff_pooledvar()
- CompareMeans.std_meandiff_separatevar()
- CompareMeans.summary()
- CompareMeans.tconfint_diff()
- CompareMeans.ttest_ind()
- CompareMeans.ttost_ind()
- CompareMeans.zconfint_diff()
- CompareMeans.ztest_ind()
- CompareMeans.ztost_ind()
- DescrStatsW.asrepeats()
- DescrStatsW.corrcoef()
- DescrStatsW.cov()
- DescrStatsW.demeaned()
- DescrStatsW.get_compare()
- DescrStatsW.mean()
- DescrStatsW.nobs()
- DescrStatsW.quantile()
- DescrStatsW.std()
- DescrStatsW.std_ddof()
- DescrStatsW.std_mean()
- DescrStatsW.sum()
- DescrStatsW.sumsquares()
- DescrStatsW.sum_weights()
- DescrStatsW.tconfint_mean()
- DescrStatsW.ttest_mean()
- DescrStatsW.ttost_mean()
- DescrStatsW.var()
- DescrStatsW.var_ddof()
- DescrStatsW.zconfint_mean()
- DescrStatsW.ztest_mean()
- DescrStatsW.ztost_mean()
- FactoredPSDMatrix.decorrelate()
- FactoredPSDMatrix.logdet()
- FactoredPSDMatrix.solve()
- FactoredPSDMatrix.to_matrix()
- FTestAnovaPower.plot_power()
- FTestAnovaPower.power()
- FTestAnovaPower.solve_power()
- FTestPower.plot_power()
- FTestPower.power()
- FTestPower.solve_power()
- GofChisquarePower.plot_power()
- GofChisquarePower.power()
- GofChisquarePower.solve_power()
- GroupsStats.groupdemean()
- GroupsStats.groupsswithin()
- GroupsStats.groupvarwithin()
- GroupsStats.runbasic()
- GroupsStats.runbasic_old()
- HetGoldfeldQuandt.run()
- Mediation.fit()
- MediationResults.summary()
- MultiComparison.allpairtest()
- MultiComparison.getranks()
- MultiComparison.kruskal()
- MultiComparison.tukeyhsd()
- NormalIndPower.plot_power()
- NormalIndPower.power()
- NormalIndPower.solve_power()
- NullDistribution.pdf()
- OLSInfluence.cooks_distance()
- OLSInfluence.cov_ratio()
- OLSInfluence.det_cov_params_not_obsi()
- OLSInfluence.dfbetas()
- OLSInfluence.dffits()
- OLSInfluence.dffits_internal()
- OLSInfluence.ess_press()
- OLSInfluence.get_resid_studentized_external()
- OLSInfluence.hat_diag_factor()
- OLSInfluence.hat_matrix_diag()
- OLSInfluence.influence()
- OLSInfluence.params_not_obsi()
- OLSInfluence.resid_press()
- OLSInfluence.resid_std()
- OLSInfluence.resid_studentized_external()
- OLSInfluence.resid_studentized_internal()
- OLSInfluence.resid_var()
- OLSInfluence.sigma2_not_obsi()
- OLSInfluence.summary_frame()
- OLSInfluence.summary_table()
- RegressionFDR.threshold()
- Runs.runs_test()
- sandbox.stats.multicomp.catstack()
- sandbox.stats.multicomp.ccols
- sandbox.stats.multicomp.compare_ordered()
- sandbox.stats.multicomp.distance_st_range()
- sandbox.stats.multicomp.ecdf()
- sandbox.stats.multicomp.get_tukeyQcrit()
- sandbox.stats.multicomp.GroupsStats()
- sandbox.stats.multicomp.homogeneous_subsets()
- sandbox.stats.multicomp.maxzero()
- sandbox.stats.multicomp.maxzerodown()
- sandbox.stats.multicomp.mcfdr()
- sandbox.stats.multicomp.MultiComparison()
- sandbox.stats.multicomp.qcrit
- sandbox.stats.multicomp.randmvn()
- sandbox.stats.multicomp.rankdata()
- sandbox.stats.multicomp.rejectionline()
- sandbox.stats.multicomp.set_partition()
- sandbox.stats.multicomp.set_remove_subs()
- sandbox.stats.multicomp.StepDown()
- sandbox.stats.multicomp.tiecorrect()
- sandbox.stats.multicomp.TukeyHSDResults()
- sandbox.stats.multicomp.varcorrection_pairs_unbalanced()
- sandbox.stats.multicomp.varcorrection_pairs_unequal()
- sandbox.stats.multicomp.varcorrection_unbalanced()
- sandbox.stats.multicomp.varcorrection_unequal()
- sandbox.stats.runs.cochrans_q()
- sandbox.stats.runs.mcnemar()
- sandbox.stats.runs.median_test_ksample()
- sandbox.stats.runs.Runs()
- sandbox.stats.runs.runstest_1samp()
- sandbox.stats.runs.runstest_2samp()
- sandbox.stats.runs.symmetry_bowker()
- stats.correlation_tools.corr_clipped()
- stats.correlation_tools.corr_nearest()
- stats.correlation_tools.corr_nearest_factor()
- stats.correlation_tools.corr_thresholded()
- stats.correlation_tools.cov_nearest()
- stats.correlation_tools.cov_nearest_factor_homog()
- stats.correlation_tools.FactoredPSDMatrix()
- stats.descriptivestats.sign_test()
- stats.diagnostic.acorr_breusch_godfrey()
- stats.diagnostic.acorr_ljungbox()
- stats.diagnostic.breaks_cusumolsresid()
- stats.diagnostic.breaks_hansen()
- stats.diagnostic.CompareCox
- stats.diagnostic.CompareJ
- stats.diagnostic.compare_cox
- stats.diagnostic.compare_j
- stats.diagnostic.HetGoldfeldQuandt
- stats.diagnostic.het_arch()
- stats.diagnostic.het_breuschpagan()
- stats.diagnostic.het_goldfeldquandt
- stats.diagnostic.het_white()
- stats.diagnostic.kstest_normal()
- stats.diagnostic.lilliefors()
- stats.diagnostic.linear_harvey_collier()
- stats.diagnostic.linear_lm()
- stats.diagnostic.linear_rainbow()
- stats.diagnostic.normal_ad()
- stats.diagnostic.recursive_olsresiduals()
- stats.diagnostic.unitroot_adf()
- stats.gof.chisquare_effectsize()
- stats.gof.gof_binning_discrete()
- stats.gof.gof_chisquare_discrete()
- stats.gof.powerdiscrepancy()
- stats.inter_rater.aggregate_raters()
- stats.inter_rater.cohens_kappa()
- stats.inter_rater.fleiss_kappa()
- stats.inter_rater.to_table()
- stats.mediation.Mediation()
- stats.mediation.MediationResults()
- stats.moment_helpers.corr2cov()
- stats.moment_helpers.cov2corr()
- stats.moment_helpers.cum2mc()
- stats.moment_helpers.mc2mnc()
- stats.moment_helpers.mc2mvsk()
- stats.moment_helpers.mnc2cum()
- stats.moment_helpers.mnc2mc()
- stats.moment_helpers.mnc2mvsk()
- stats.moment_helpers.mvsk2mc()
- stats.moment_helpers.mvsk2mnc()
- stats.moment_helpers.se_cov()
- stats.multicomp.pairwise_tukeyhsd()
- stats.multitest.fdrcorrection()
- stats.multitest.fdrcorrection_twostage()
- stats.multitest.local_fdr()
- stats.multitest.multipletests()
- stats.multitest.NullDistribution()
- stats.multitest.RegressionFDR()
- stats.outliers_influence.OLSInfluence()
- stats.outliers_influence.variance_inflation_factor()
- stats.power.FTestAnovaPower()
- stats.power.FTestPower()
- stats.power.GofChisquarePower()
- stats.power.NormalIndPower()
- stats.power.TTestIndPower()
- stats.power.TTestPower()
- stats.power.tt_ind_solve_power
- stats.power.tt_solve_power
- stats.power.zt_ind_solve_power
- stats.proportion.binom_test()
- stats.proportion.binom_test_reject_interval()
- stats.proportion.binom_tost()
- stats.proportion.binom_tost_reject_interval()
- stats.proportion.multinomial_proportions_confint()
- stats.proportion.power_binom_tost()
- stats.proportion.power_ztost_prop()
- stats.proportion.proportions_chisquare()
- stats.proportion.proportions_chisquare_allpairs()
- stats.proportion.proportions_chisquare_pairscontrol()
- stats.proportion.proportions_ztest()
- stats.proportion.proportions_ztost()
- stats.proportion.proportion_confint()
- stats.proportion.proportion_effectsize()
- stats.proportion.samplesize_confint_proportion()
- stats.sandwich_covariance.cov_cluster()
- stats.sandwich_covariance.cov_cluster_2groups()
- stats.sandwich_covariance.cov_hac()
- stats.sandwich_covariance.cov_hc0()
- stats.sandwich_covariance.cov_hc1()
- stats.sandwich_covariance.cov_hc2()
- stats.sandwich_covariance.cov_hc3()
- stats.sandwich_covariance.cov_nw_groupsum()
- stats.sandwich_covariance.cov_nw_panel()
- stats.sandwich_covariance.cov_white_simple()
- stats.sandwich_covariance.se_cov()
- stats.stattools.durbin_watson()
- stats.stattools.expected_robust_kurtosis()
- stats.stattools.jarque_bera()
- stats.stattools.medcouple()
- stats.stattools.omni_normtest()
- stats.stattools.robust_kurtosis()
- stats.stattools.robust_skewness()
- stats.weightstats.CompareMeans()
- stats.weightstats.DescrStatsW()
- stats.weightstats.ttest_ind()
- stats.weightstats.ttost_ind()
- stats.weightstats.ttost_paired()
- stats.weightstats.zconfint()
- stats.weightstats.ztest()
- stats.weightstats.ztost()
- stats.weightstats._tconfint_generic()
- stats.weightstats._tstat_generic()
- stats.weightstats._zconfint_generic()
- stats.weightstats._zstat_generic()
- stats.weightstats._zstat_generic2()
- StepDown.check_set()
- StepDown.get_crit()
- StepDown.get_distance_matrix()
- StepDown.iter_subsets()
- StepDown.run()
- StepDown.stepdown()
- TTestIndPower.plot_power()
- TTestIndPower.power()
- TTestIndPower.solve_power()
- TTestPower.plot_power()
- TTestPower.power()
- TTestPower.solve_power()
- TukeyHSDResults.plot_simultaneous()
- TukeyHSDResults.summary()
Time Series analysis
- AR.fit()
- AR.from_formula()
- AR.hessian()
- AR.information()
- AR.initialize()
- AR.loglike()
- AR.predict()
- AR.score()
- AR.select_order()
- ARIMA.fit()
- ARIMA.from_formula()
- ARIMA.geterrors()
- ARIMA.hessian()
- ARIMA.information()
- ARIMA.initialize()
- ARIMA.loglike()
- ARIMA.loglike_css()
- ARIMA.loglike_kalman()
- ARIMA.predict()
- ARIMA.score()
- ARIMAResults.aic()
- ARIMAResults.arfreq()
- ARIMAResults.arparams()
- ARIMAResults.arroots()
- ARIMAResults.bic()
- ARIMAResults.bse()
- ARIMAResults.conf_int()
- ARIMAResults.cov_params()
- ARIMAResults.fittedvalues()
- ARIMAResults.forecast()
- ARIMAResults.f_test()
- ARIMAResults.hqic()
- ARIMAResults.initialize()
- ARIMAResults.llf()
- ARIMAResults.load()
- ARIMAResults.mafreq()
- ARIMAResults.maparams()
- ARIMAResults.maroots()
- ARIMAResults.normalized_cov_params()
- ARIMAResults.plot_predict()
- ARIMAResults.predict()
- ARIMAResults.pvalues()
- ARIMAResults.remove_data()
- ARIMAResults.resid()
- ARIMAResults.save()
- ARIMAResults.summary()
- ARIMAResults.summary2()
- ARIMAResults.tvalues()
- ARIMAResults.t_test()
- ARIMAResults.t_test_pairwise()
- ARIMAResults.wald_test()
- ARIMAResults.wald_test_terms()
- ARMA.fit()
- ARMA.from_formula()
- ARMA.geterrors()
- ARMA.hessian()
- ARMA.information()
- ARMA.initialize()
- ARMA.loglike()
- ARMA.loglike_css()
- ARMA.loglike_kalman()
- ARMA.predict()
- ARMA.score()
- ArmaFft.acf()
- ArmaFft.acf2spdfreq()
- ArmaFft.acovf()
- ArmaFft.arma2ar()
- ArmaFft.arma2ma()
- ArmaFft.fftar()
- ArmaFft.fftarma()
- ArmaFft.fftma()
- ArmaFft.filter()
- ArmaFft.filter2()
- ArmaFft.from_coeffs()
- ArmaFft.from_estimation()
- ArmaFft.generate_sample()
- ArmaFft.impulse_response()
- ArmaFft.invertroots()
- ArmaFft.invpowerspd()
- ArmaFft.pacf()
- ArmaFft.pad()
- ArmaFft.padarr()
- ArmaFft.periodogram()
- ArmaFft.plot4()
- ArmaFft.spd()
- ArmaFft.spddirect()
- ArmaFft.spdmapoly()
- ArmaFft.spdpoly()
- ArmaFft.spdroots()
- ArmaFft.spdshift()
- ArmaProcess.acf()
- ArmaProcess.acovf()
- ArmaProcess.arma2ar()
- ArmaProcess.arma2ma()
- ArmaProcess.from_coeffs()
- ArmaProcess.from_estimation()
- ArmaProcess.generate_sample()
- ArmaProcess.impulse_response()
- ArmaProcess.invertroots()
- ArmaProcess.pacf()
- ArmaProcess.periodogram()
- ARMAResults.aic()
- ARMAResults.arfreq()
- ARMAResults.arparams()
- ARMAResults.arroots()
- ARMAResults.bic()
- ARMAResults.bse()
- ARMAResults.conf_int()
- ARMAResults.cov_params()
- ARMAResults.fittedvalues()
- ARMAResults.forecast()
- ARMAResults.f_test()
- ARMAResults.hqic()
- ARMAResults.initialize()
- ARMAResults.llf()
- ARMAResults.load()
- ARMAResults.mafreq()
- ARMAResults.maparams()
- ARMAResults.maroots()
- ARMAResults.normalized_cov_params()
- ARMAResults.plot_predict()
- ARMAResults.predict()
- ARMAResults.pvalues()
- ARMAResults.remove_data()
- ARMAResults.resid()
- ARMAResults.save()
- ARMAResults.summary()
- ARMAResults.summary2()
- ARMAResults.tvalues()
- ARMAResults.t_test()
- ARMAResults.t_test_pairwise()
- ARMAResults.wald_test()
- ARMAResults.wald_test_terms()
- ARResults.aic()
- ARResults.bic()
- ARResults.bse()
- ARResults.conf_int()
- ARResults.cov_params()
- ARResults.fittedvalues()
- ARResults.fpe()
- ARResults.f_test()
- ARResults.hqic()
- ARResults.initialize()
- ARResults.llf()
- ARResults.load()
- ARResults.normalized_cov_params()
- ARResults.predict()
- ARResults.pvalues()
- ARResults.remove_data()
- ARResults.resid()
- ARResults.roots()
- ARResults.save()
- ARResults.scale()
- ARResults.sigma2()
- ARResults.summary()
- ARResults.tvalues()
- ARResults.t_test()
- ARResults.t_test_pairwise()
- ARResults.wald_test()
- ARResults.wald_test_terms()
- CausalityTestResults.summary()
- CointRankResults.summary()
- DynamicVAR.coefs()
- DynamicVAR.equations()
- DynamicVAR.forecast()
- DynamicVAR.plot_forecast()
- DynamicVAR.r2()
- DynamicVAR.resid()
- DynamicVAR.T()
- ExponentialSmoothing.fit()
- ExponentialSmoothing.from_formula()
- ExponentialSmoothing.hessian()
- ExponentialSmoothing.information()
- ExponentialSmoothing.initialize()
- ExponentialSmoothing.loglike()
- ExponentialSmoothing.predict()
- ExponentialSmoothing.score()
- FEVD.cov()
- FEVD.plot()
- FEVD.summary()
- Holt.fit()
- Holt.from_formula()
- Holt.hessian()
- Holt.information()
- Holt.initialize()
- Holt.loglike()
- Holt.predict()
- Holt.score()
- HoltWintersResults.forecast()
- HoltWintersResults.initialize()
- HoltWintersResults.predict()
- HoltWintersResults.summary()
- HypothesisTestResults.summary()
- IRAnalysis.cov()
- IRAnalysis.cum_effect_cov()
- IRAnalysis.cum_effect_stderr()
- IRAnalysis.cum_errband_mc()
- IRAnalysis.errband_mc()
- IRAnalysis.err_band_sz1()
- IRAnalysis.err_band_sz2()
- IRAnalysis.err_band_sz3()
- IRAnalysis.fevd_table()
- IRAnalysis.G()
- IRAnalysis.H()
- IRAnalysis.lr_effect_cov()
- IRAnalysis.lr_effect_stderr()
- IRAnalysis.plot()
- IRAnalysis.plot_cum_effects()
- IRAnalysis.stderr()
- KalmanFilter.geterrors()
- KalmanFilter.loglike()
- KalmanFilter.R()
- KalmanFilter.T()
- KalmanFilter.Z()
- LagOrderResults.summary()
- MarkovAutoregression.filter()
- MarkovAutoregression.fit()
- MarkovAutoregression.from_formula()
- MarkovAutoregression.hessian()
- MarkovAutoregression.information()
- MarkovAutoregression.initialize()
- MarkovAutoregression.initialize_known()
- MarkovAutoregression.initialize_steady_state()
- MarkovAutoregression.initial_probabilities()
- MarkovAutoregression.loglike()
- MarkovAutoregression.loglikeobs()
- MarkovAutoregression.predict()
- MarkovAutoregression.predict_conditional()
- MarkovAutoregression.regime_transition_matrix()
- MarkovAutoregression.score()
- MarkovAutoregression.score_obs()
- MarkovAutoregression.smooth()
- MarkovAutoregression.transform_params()
- MarkovAutoregression.untransform_params()
- MarkovRegression.filter()
- MarkovRegression.fit()
- MarkovRegression.from_formula()
- MarkovRegression.hessian()
- MarkovRegression.information()
- MarkovRegression.initialize()
- MarkovRegression.initialize_known()
- MarkovRegression.initialize_steady_state()
- MarkovRegression.initial_probabilities()
- MarkovRegression.loglike()
- MarkovRegression.loglikeobs()
- MarkovRegression.predict()
- MarkovRegression.predict_conditional()
- MarkovRegression.regime_transition_matrix()
- MarkovRegression.score()
- MarkovRegression.score_obs()
- MarkovRegression.smooth()
- MarkovRegression.transform_params()
- MarkovRegression.untransform_params()
- NormalityTestResults.summary()
- sandbox.tsa.fftarma.ArmaFft()
- SimpleExpSmoothing.fit()
- SimpleExpSmoothing.from_formula()
- SimpleExpSmoothing.hessian()
- SimpleExpSmoothing.information()
- SimpleExpSmoothing.initialize()
- SimpleExpSmoothing.loglike()
- SimpleExpSmoothing.predict()
- SimpleExpSmoothing.score()
- tsa.arima_model.ARIMA()
- tsa.arima_model.ARIMAResults()
- tsa.arima_model.ARMA()
- tsa.arima_model.ARMAResults()
- tsa.arima_process.ar2arma()
- tsa.arima_process.arma2ar()
- tsa.arima_process.arma2ma()
- tsa.arima_process.ArmaProcess()
- tsa.arima_process.arma_acf()
- tsa.arima_process.arma_acovf()
- tsa.arima_process.arma_generate_sample()
- tsa.arima_process.arma_impulse_response()
- tsa.arima_process.arma_pacf()
- tsa.arima_process.arma_periodogram()
- tsa.arima_process.deconvolve()
- tsa.arima_process.index2lpol()
- tsa.arima_process.lpol2index()
- tsa.arima_process.lpol_fiar()
- tsa.arima_process.lpol_fima()
- tsa.arima_process.lpol_sdiff()
- tsa.ar_model.AR()
- tsa.ar_model.ARResults()
- tsa.filters.bk_filter.bkfilter()
- tsa.filters.cf_filter.cffilter()
- tsa.filters.filtertools.convolution_filter()
- tsa.filters.filtertools.fftconvolve3()
- tsa.filters.filtertools.fftconvolveinv()
- tsa.filters.filtertools.miso_lfilter()
- tsa.filters.filtertools.recursive_filter()
- tsa.filters.hp_filter.hpfilter()
- tsa.holtwinters.ExponentialSmoothing()
- tsa.holtwinters.Holt()
- tsa.holtwinters.HoltWintersResults()
- tsa.holtwinters.SimpleExpSmoothing()
- tsa.interp.denton.dentonm()
- tsa.kalmanf.kalmanfilter.KalmanFilter
- tsa.regime_switching.markov_autoregression.MarkovAutoregression()
- tsa.regime_switching.markov_regression.MarkovRegression()
- tsa.seasonal.seasonal_decompose()
- tsa.stattools.acf()
- tsa.stattools.acovf()
- tsa.stattools.adfuller()
- tsa.stattools.arma_order_select_ic()
- tsa.stattools.bds()
- tsa.stattools.ccf()
- tsa.stattools.ccovf()
- tsa.stattools.coint()
- tsa.stattools.grangercausalitytests()
- tsa.stattools.kpss()
- tsa.stattools.levinson_durbin()
- tsa.stattools.pacf()
- tsa.stattools.pacf_ols()
- tsa.stattools.pacf_yw()
- tsa.stattools.periodogram()
- tsa.stattools.q_stat()
- tsa.tsatools.add_trend()
- tsa.tsatools.detrend()
- tsa.tsatools.lagmat()
- tsa.tsatools.lagmat2ds()
- tsa.varma_process.VarmaPoly()
- tsa.vector_ar.dynamic.DynamicVAR()
- tsa.vector_ar.hypothesis_test_results.CausalityTestResults()
- tsa.vector_ar.hypothesis_test_results.HypothesisTestResults()
- tsa.vector_ar.hypothesis_test_results.NormalityTestResults()
- tsa.vector_ar.hypothesis_test_results.WhitenessTestResults()
- tsa.vector_ar.irf.IRAnalysis()
- tsa.vector_ar.var_model.FEVD()
- tsa.vector_ar.var_model.LagOrderResults()
- tsa.vector_ar.var_model.VAR()
- tsa.vector_ar.var_model.VARProcess()
- tsa.vector_ar.var_model.VARResults()
- tsa.vector_ar.vecm.CointRankResults()
- tsa.vector_ar.vecm.coint_johansen()
- tsa.vector_ar.vecm.select_coint_rank()
- tsa.vector_ar.vecm.select_order()
- tsa.vector_ar.vecm.VECM()
- tsa.vector_ar.vecm.VECMResults()
- tsa.x13.x13_arima_analysis()
- tsa.x13.x13_arima_select_order()
- VAR.fit()
- VAR.from_formula()
- VAR.hessian()
- VAR.information()
- VAR.initialize()
- VAR.loglike()
- VAR.predict()
- VAR.score()
- VAR.select_order()
- VarmaPoly.getisinvertible()
- VarmaPoly.getisstationary()
- VarmaPoly.hstack()
- VarmaPoly.hstackarma_minus1()
- VarmaPoly.reduceform()
- VarmaPoly.stacksquare()
- VarmaPoly.vstack()
- VarmaPoly.vstackarma_minus1()
- VARProcess.acf()
- VARProcess.acorr()
- VARProcess.forecast()
- VARProcess.forecast_cov()
- VARProcess.forecast_interval()
- VARProcess.get_eq_index()
- VARProcess.intercept_longrun()
- VARProcess.is_stable()
- VARProcess.long_run_effects()
- VARProcess.ma_rep()
- VARProcess.mean()
- VARProcess.mse()
- VARProcess.orth_ma_rep()
- VARProcess.plotsim()
- VARProcess.plot_acorr()
- VARProcess.simulate_var()
- VARProcess.to_vecm()
- VARResults.acf()
- VARResults.acorr()
- VARResults.bse()
- VARResults.cov_params()
- VARResults.cov_ybar()
- VARResults.detomega()
- VARResults.fevd()
- VARResults.fittedvalues()
- VARResults.forecast()
- VARResults.forecast_cov()
- VARResults.forecast_interval()
- VARResults.get_eq_index()
- VARResults.info_criteria()
- VARResults.intercept_longrun()
- VARResults.irf()
- VARResults.irf_errband_mc()
- VARResults.irf_resim()
- VARResults.is_stable()
- VARResults.llf()
- VARResults.long_run_effects()
- VARResults.ma_rep()
- VARResults.mean()
- VARResults.mse()
- VARResults.orth_ma_rep()
- VARResults.plot()
- VARResults.plotsim()
- VARResults.plot_acorr()
- VARResults.plot_forecast()
- VARResults.plot_sample_acorr()
- VARResults.pvalues()
- VARResults.pvalues_dt()
- VARResults.pvalues_endog_lagged()
- VARResults.reorder()
- VARResults.resid()
- VARResults.resid_acorr()
- VARResults.resid_acov()
- VARResults.resid_corr()
- VARResults.roots()
- VARResults.sample_acorr()
- VARResults.sample_acov()
- VARResults.sigma_u_mle()
- VARResults.simulate_var()
- VARResults.stderr()
- VARResults.stderr_dt()
- VARResults.stderr_endog_lagged()
- VARResults.summary()
- VARResults.test_causality()
- VARResults.test_inst_causality()
- VARResults.test_normality()
- VARResults.test_whiteness()
- VARResults.to_vecm()
- VARResults.tvalues()
- VARResults.tvalues_dt()
- VARResults.tvalues_endog_lagged()
- VECM.fit()
- VECM.from_formula()
- VECM.hessian()
- VECM.information()
- VECM.initialize()
- VECM.loglike()
- VECM.predict()
- VECM.score()
- VECMResults.conf_int_alpha()
- VECMResults.conf_int_beta()
- VECMResults.conf_int_det_coef()
- VECMResults.conf_int_det_coef_coint()
- VECMResults.conf_int_gamma()
- VECMResults.cov_params_default()
- VECMResults.cov_params_wo_det()
- VECMResults.cov_var_repr()
- VECMResults.fittedvalues()
- VECMResults.irf()
- VECMResults.llf()
- VECMResults.ma_rep()
- VECMResults.orth_ma_rep()
- VECMResults.plot_data()
- VECMResults.plot_forecast()
- VECMResults.predict()
- VECMResults.pvalues_alpha()
- VECMResults.pvalues_beta()
- VECMResults.pvalues_det_coef()
- VECMResults.pvalues_det_coef_coint()
- VECMResults.pvalues_gamma()
- VECMResults.resid()
- VECMResults.stderr_alpha()
- VECMResults.stderr_beta()
- VECMResults.stderr_coint()
- VECMResults.stderr_det_coef()
- VECMResults.stderr_det_coef_coint()
- VECMResults.stderr_gamma()
- VECMResults.stderr_params()
- VECMResults.summary()
- VECMResults.test_granger_causality()
- VECMResults.test_inst_causality()
- VECMResults.test_normality()
- VECMResults.test_whiteness()
- VECMResults.tvalues_alpha()
- VECMResults.tvalues_beta()
- VECMResults.tvalues_det_coef()
- VECMResults.tvalues_det_coef_coint()
- VECMResults.tvalues_gamma()
- VECMResults.var_rep()
- WhitenessTestResults.summary()
Time Series Analysis by State Space Methods
- DynamicFactor.filter()
- DynamicFactor.fit()
- DynamicFactor.from_formula()
- DynamicFactor.hessian()
- DynamicFactor.impulse_responses()
- DynamicFactor.information()
- DynamicFactor.initialize()
- DynamicFactor.initialize_approximate_diffuse()
- DynamicFactor.initialize_known()
- DynamicFactor.initialize_statespace()
- DynamicFactor.initialize_stationary()
- DynamicFactor.loglike()
- DynamicFactor.loglikeobs()
- DynamicFactor.observed_information_matrix()
- DynamicFactor.opg_information_matrix()
- DynamicFactor.predict()
- DynamicFactor.prepare_data()
- DynamicFactor.score()
- DynamicFactor.score_obs()
- DynamicFactor.set_conserve_memory()
- DynamicFactor.set_filter_method()
- DynamicFactor.set_inversion_method()
- DynamicFactor.set_smoother_output()
- DynamicFactor.set_stability_method()
- DynamicFactor.simulate()
- DynamicFactor.simulation_smoother()
- DynamicFactor.smooth()
- DynamicFactor.transform_jacobian()
- DynamicFactor.transform_params()
- DynamicFactor.untransform_params()
- DynamicFactor.update()
- DynamicFactorResults.aic()
- DynamicFactorResults.bic()
- DynamicFactorResults.bse()
- DynamicFactorResults.coefficients_of_determination()
- DynamicFactorResults.conf_int()
- DynamicFactorResults.cov_params()
- DynamicFactorResults.cov_params_approx()
- DynamicFactorResults.cov_params_oim()
- DynamicFactorResults.cov_params_opg()
- DynamicFactorResults.cov_params_robust()
- DynamicFactorResults.cov_params_robust_approx()
- DynamicFactorResults.cov_params_robust_oim()
- DynamicFactorResults.fittedvalues()
- DynamicFactorResults.forecast()
- DynamicFactorResults.f_test()
- DynamicFactorResults.get_forecast()
- DynamicFactorResults.get_prediction()
- DynamicFactorResults.hqic()
- DynamicFactorResults.impulse_responses()
- DynamicFactorResults.info_criteria()
- DynamicFactorResults.initialize()
- DynamicFactorResults.llf()
- DynamicFactorResults.llf_obs()
- DynamicFactorResults.load()
- DynamicFactorResults.loglikelihood_burn()
- DynamicFactorResults.normalized_cov_params()
- DynamicFactorResults.plot_coefficients_of_determination()
- DynamicFactorResults.plot_diagnostics()
- DynamicFactorResults.predict()
- DynamicFactorResults.pvalues()
- DynamicFactorResults.remove_data()
- DynamicFactorResults.resid()
- DynamicFactorResults.save()
- DynamicFactorResults.simulate()
- DynamicFactorResults.summary()
- DynamicFactorResults.test_heteroskedasticity()
- DynamicFactorResults.test_normality()
- DynamicFactorResults.test_serial_correlation()
- DynamicFactorResults.tvalues()
- DynamicFactorResults.t_test()
- DynamicFactorResults.t_test_pairwise()
- DynamicFactorResults.wald_test()
- DynamicFactorResults.wald_test_terms()
- DynamicFactorResults.zvalues()
- FilterResults.predict()
- FilterResults.update_filter()
- FilterResults.update_representation()
- FrozenRepresentation.update_representation()
- KalmanFilter.bind()
- KalmanFilter.filter()
- KalmanFilter.impulse_responses()
- KalmanFilter.initialize_approximate_diffuse()
- KalmanFilter.initialize_known()
- KalmanFilter.initialize_stationary()
- KalmanFilter.loglike()
- KalmanFilter.loglikeobs()
- KalmanFilter.set_conserve_memory()
- KalmanFilter.set_filter_method()
- KalmanFilter.set_filter_timing()
- KalmanFilter.set_inversion_method()
- KalmanFilter.set_stability_method()
- KalmanFilter.simulate()
- KalmanSmoother.bind()
- KalmanSmoother.filter()
- KalmanSmoother.impulse_responses()
- KalmanSmoother.initialize_approximate_diffuse()
- KalmanSmoother.initialize_known()
- KalmanSmoother.initialize_stationary()
- KalmanSmoother.loglike()
- KalmanSmoother.loglikeobs()
- KalmanSmoother.set_conserve_memory()
- KalmanSmoother.set_filter_method()
- KalmanSmoother.set_filter_timing()
- KalmanSmoother.set_inversion_method()
- KalmanSmoother.set_smoother_output()
- KalmanSmoother.set_smooth_method()
- KalmanSmoother.set_stability_method()
- KalmanSmoother.simulate()
- KalmanSmoother.smooth()
- MLEModel.filter()
- MLEModel.fit()
- MLEModel.from_formula()
- MLEModel.hessian()
- MLEModel.impulse_responses()
- MLEModel.information()
- MLEModel.initialize()
- MLEModel.initialize_approximate_diffuse()
- MLEModel.initialize_known()
- MLEModel.initialize_statespace()
- MLEModel.initialize_stationary()
- MLEModel.loglike()
- MLEModel.loglikeobs()
- MLEModel.observed_information_matrix()
- MLEModel.opg_information_matrix()
- MLEModel.predict()
- MLEModel.prepare_data()
- MLEModel.score()
- MLEModel.score_obs()
- MLEModel.set_conserve_memory()
- MLEModel.set_filter_method()
- MLEModel.set_inversion_method()
- MLEModel.set_smoother_output()
- MLEModel.set_stability_method()
- MLEModel.simulate()
- MLEModel.simulation_smoother()
- MLEModel.smooth()
- MLEModel.transform_jacobian()
- MLEModel.transform_params()
- MLEModel.untransform_params()
- MLEModel.update()
- MLEResults.aic()
- MLEResults.bic()
- MLEResults.bse()
- MLEResults.conf_int()
- MLEResults.cov_params()
- MLEResults.cov_params_approx()
- MLEResults.cov_params_oim()
- MLEResults.cov_params_opg()
- MLEResults.cov_params_robust()
- MLEResults.cov_params_robust_approx()
- MLEResults.cov_params_robust_oim()
- MLEResults.fittedvalues()
- MLEResults.forecast()
- MLEResults.f_test()
- MLEResults.get_forecast()
- MLEResults.get_prediction()
- MLEResults.hqic()
- MLEResults.impulse_responses()
- MLEResults.info_criteria()
- MLEResults.initialize()
- MLEResults.llf()
- MLEResults.llf_obs()
- MLEResults.load()
- MLEResults.loglikelihood_burn()
- MLEResults.normalized_cov_params()
- MLEResults.plot_diagnostics()
- MLEResults.predict()
- MLEResults.pvalues()
- MLEResults.remove_data()
- MLEResults.resid()
- MLEResults.save()
- MLEResults.simulate()
- MLEResults.summary()
- MLEResults.test_heteroskedasticity()
- MLEResults.test_normality()
- MLEResults.test_serial_correlation()
- MLEResults.tvalues()
- MLEResults.t_test()
- MLEResults.t_test_pairwise()
- MLEResults.wald_test()
- MLEResults.wald_test_terms()
- MLEResults.zvalues()
- PredictionResults.predict()
- PredictionResults.update_filter()
- PredictionResults.update_representation()
- Representation.bind()
- Representation.initialize_approximate_diffuse()
- Representation.initialize_known()
- Representation.initialize_stationary()
- SARIMAX.filter()
- SARIMAX.fit()
- SARIMAX.from_formula()
- SARIMAX.hessian()
- SARIMAX.impulse_responses()
- SARIMAX.information()
- SARIMAX.initialize()
- SARIMAX.initialize_approximate_diffuse()
- SARIMAX.initialize_known()
- SARIMAX.initialize_state()
- SARIMAX.initialize_statespace()
- SARIMAX.initialize_stationary()
- SARIMAX.loglike()
- SARIMAX.loglikeobs()
- SARIMAX.observed_information_matrix()
- SARIMAX.opg_information_matrix()
- SARIMAX.predict()
- SARIMAX.prepare_data()
- SARIMAX.score()
- SARIMAX.score_obs()
- SARIMAX.set_conserve_memory()
- SARIMAX.set_filter_method()
- SARIMAX.set_inversion_method()
- SARIMAX.set_smoother_output()
- SARIMAX.set_stability_method()
- SARIMAX.simulate()
- SARIMAX.simulation_smoother()
- SARIMAX.smooth()
- SARIMAX.transform_jacobian()
- SARIMAX.transform_params()
- SARIMAX.untransform_params()
- SARIMAX.update()
- SARIMAXResults.aic()
- SARIMAXResults.arfreq()
- SARIMAXResults.arparams()
- SARIMAXResults.arroots()
- SARIMAXResults.bic()
- SARIMAXResults.bse()
- SARIMAXResults.conf_int()
- SARIMAXResults.cov_params()
- SARIMAXResults.cov_params_approx()
- SARIMAXResults.cov_params_oim()
- SARIMAXResults.cov_params_opg()
- SARIMAXResults.cov_params_robust()
- SARIMAXResults.cov_params_robust_approx()
- SARIMAXResults.cov_params_robust_oim()
- SARIMAXResults.fittedvalues()
- SARIMAXResults.forecast()
- SARIMAXResults.f_test()
- SARIMAXResults.get_forecast()
- SARIMAXResults.get_prediction()
- SARIMAXResults.hqic()
- SARIMAXResults.impulse_responses()
- SARIMAXResults.info_criteria()
- SARIMAXResults.initialize()
- SARIMAXResults.llf()
- SARIMAXResults.llf_obs()
- SARIMAXResults.load()
- SARIMAXResults.loglikelihood_burn()
- SARIMAXResults.mafreq()
- SARIMAXResults.maparams()
- SARIMAXResults.maroots()
- SARIMAXResults.normalized_cov_params()
- SARIMAXResults.plot_diagnostics()
- SARIMAXResults.predict()
- SARIMAXResults.pvalues()
- SARIMAXResults.remove_data()
- SARIMAXResults.resid()
- SARIMAXResults.save()
- SARIMAXResults.seasonalarparams()
- SARIMAXResults.seasonalmaparams()
- SARIMAXResults.simulate()
- SARIMAXResults.summary()
- SARIMAXResults.test_heteroskedasticity()
- SARIMAXResults.test_normality()
- SARIMAXResults.test_serial_correlation()
- SARIMAXResults.tvalues()
- SARIMAXResults.t_test()
- SARIMAXResults.t_test_pairwise()
- SARIMAXResults.wald_test()
- SARIMAXResults.wald_test_terms()
- SARIMAXResults.zvalues()
- SmootherResults.predict()
- SmootherResults.update_filter()
- SmootherResults.update_representation()
- SmootherResults.update_smoother()
- tsa.statespace.dynamic_factor.DynamicFactor()
- tsa.statespace.dynamic_factor.DynamicFactorResults()
- tsa.statespace.kalman_filter.FilterResults()
- tsa.statespace.kalman_filter.KalmanFilter()
- tsa.statespace.kalman_filter.PredictionResults()
- tsa.statespace.kalman_smoother.KalmanSmoother()
- tsa.statespace.kalman_smoother.SmootherResults()
- tsa.statespace.mlemodel.MLEModel()
- tsa.statespace.mlemodel.MLEResults()
- tsa.statespace.representation.FrozenRepresentation()
- tsa.statespace.representation.Representation()
- tsa.statespace.sarimax.SARIMAX()
- tsa.statespace.sarimax.SARIMAXResults()
- tsa.statespace.structural.UnobservedComponents()
- tsa.statespace.structural.UnobservedComponentsResults()
- tsa.statespace.tools.companion_matrix()
- tsa.statespace.tools.constrain_stationary_multivariate()
- tsa.statespace.tools.constrain_stationary_univariate()
- tsa.statespace.tools.diff()
- tsa.statespace.tools.is_invertible()
- tsa.statespace.tools.unconstrain_stationary_multivariate()
- tsa.statespace.tools.unconstrain_stationary_univariate()
- tsa.statespace.tools.validate_matrix_shape()
- tsa.statespace.tools.validate_vector_shape()
- tsa.statespace.varmax.VARMAX()
- tsa.statespace.varmax.VARMAXResults()
- UnobservedComponents.filter()
- UnobservedComponents.fit()
- UnobservedComponents.from_formula()
- UnobservedComponents.hessian()
- UnobservedComponents.impulse_responses()
- UnobservedComponents.information()
- UnobservedComponents.initialize()
- UnobservedComponents.initialize_approximate_diffuse()
- UnobservedComponents.initialize_known()
- UnobservedComponents.initialize_state()
- UnobservedComponents.initialize_statespace()
- UnobservedComponents.initialize_stationary()
- UnobservedComponents.loglike()
- UnobservedComponents.loglikeobs()
- UnobservedComponents.observed_information_matrix()
- UnobservedComponents.opg_information_matrix()
- UnobservedComponents.predict()
- UnobservedComponents.prepare_data()
- UnobservedComponents.score()
- UnobservedComponents.score_obs()
- UnobservedComponents.setup()
- UnobservedComponents.set_conserve_memory()
- UnobservedComponents.set_filter_method()
- UnobservedComponents.set_inversion_method()
- UnobservedComponents.set_smoother_output()
- UnobservedComponents.set_stability_method()
- UnobservedComponents.simulate()
- UnobservedComponents.simulation_smoother()
- UnobservedComponents.smooth()
- UnobservedComponents.transform_jacobian()
- UnobservedComponents.transform_params()
- UnobservedComponents.untransform_params()
- UnobservedComponents.update()
- UnobservedComponentsResults.aic()
- UnobservedComponentsResults.bic()
- UnobservedComponentsResults.bse()
- UnobservedComponentsResults.conf_int()
- UnobservedComponentsResults.cov_params()
- UnobservedComponentsResults.cov_params_approx()
- UnobservedComponentsResults.cov_params_oim()
- UnobservedComponentsResults.cov_params_opg()
- UnobservedComponentsResults.cov_params_robust()
- UnobservedComponentsResults.cov_params_robust_approx()
- UnobservedComponentsResults.cov_params_robust_oim()
- UnobservedComponentsResults.fittedvalues()
- UnobservedComponentsResults.forecast()
- UnobservedComponentsResults.f_test()
- UnobservedComponentsResults.get_forecast()
- UnobservedComponentsResults.get_prediction()
- UnobservedComponentsResults.hqic()
- UnobservedComponentsResults.impulse_responses()
- UnobservedComponentsResults.info_criteria()
- UnobservedComponentsResults.initialize()
- UnobservedComponentsResults.llf()
- UnobservedComponentsResults.llf_obs()
- UnobservedComponentsResults.load()
- UnobservedComponentsResults.loglikelihood_burn()
- UnobservedComponentsResults.normalized_cov_params()
- UnobservedComponentsResults.plot_components()
- UnobservedComponentsResults.plot_diagnostics()
- UnobservedComponentsResults.predict()
- UnobservedComponentsResults.pvalues()
- UnobservedComponentsResults.remove_data()
- UnobservedComponentsResults.resid()
- UnobservedComponentsResults.save()
- UnobservedComponentsResults.simulate()
- UnobservedComponentsResults.summary()
- UnobservedComponentsResults.test_heteroskedasticity()
- UnobservedComponentsResults.test_normality()
- UnobservedComponentsResults.test_serial_correlation()
- UnobservedComponentsResults.tvalues()
- UnobservedComponentsResults.t_test()
- UnobservedComponentsResults.t_test_pairwise()
- UnobservedComponentsResults.wald_test()
- UnobservedComponentsResults.wald_test_terms()
- UnobservedComponentsResults.zvalues()
- VARMAX.filter()
- VARMAX.fit()
- VARMAX.from_formula()
- VARMAX.hessian()
- VARMAX.impulse_responses()
- VARMAX.information()
- VARMAX.initialize()
- VARMAX.initialize_approximate_diffuse()
- VARMAX.initialize_known()
- VARMAX.initialize_statespace()
- VARMAX.initialize_stationary()
- VARMAX.loglike()
- VARMAX.loglikeobs()
- VARMAX.observed_information_matrix()
- VARMAX.opg_information_matrix()
- VARMAX.predict()
- VARMAX.prepare_data()
- VARMAX.score()
- VARMAX.score_obs()
- VARMAX.set_conserve_memory()
- VARMAX.set_filter_method()
- VARMAX.set_inversion_method()
- VARMAX.set_smoother_output()
- VARMAX.set_stability_method()
- VARMAX.simulate()
- VARMAX.simulation_smoother()
- VARMAX.smooth()
- VARMAX.transform_jacobian()
- VARMAX.transform_params()
- VARMAX.untransform_params()
- VARMAX.update()
- VARMAXResults.aic()
- VARMAXResults.bic()
- VARMAXResults.bse()
- VARMAXResults.conf_int()
- VARMAXResults.cov_params()
- VARMAXResults.cov_params_approx()
- VARMAXResults.cov_params_oim()
- VARMAXResults.cov_params_opg()
- VARMAXResults.cov_params_robust()
- VARMAXResults.cov_params_robust_approx()
- VARMAXResults.cov_params_robust_oim()
- VARMAXResults.fittedvalues()
- VARMAXResults.forecast()
- VARMAXResults.f_test()
- VARMAXResults.get_forecast()
- VARMAXResults.get_prediction()
- VARMAXResults.hqic()
- VARMAXResults.impulse_responses()
- VARMAXResults.info_criteria()
- VARMAXResults.initialize()
- VARMAXResults.llf()
- VARMAXResults.llf_obs()
- VARMAXResults.load()
- VARMAXResults.loglikelihood_burn()
- VARMAXResults.normalized_cov_params()
- VARMAXResults.plot_diagnostics()
- VARMAXResults.predict()
- VARMAXResults.pvalues()
- VARMAXResults.remove_data()
- VARMAXResults.resid()
- VARMAXResults.save()
- VARMAXResults.simulate()
- VARMAXResults.summary()
- VARMAXResults.test_heteroskedasticity()
- VARMAXResults.test_normality()
- VARMAXResults.test_serial_correlation()
- VARMAXResults.tvalues()
- VARMAXResults.t_test()
- VARMAXResults.t_test_pairwise()
- VARMAXResults.wald_test()
- VARMAXResults.wald_test_terms()
- VARMAXResults.zvalues()
Tools
- tools.eval_measures.aic()
- tools.eval_measures.aicc()
- tools.eval_measures.aicc_sigma()
- tools.eval_measures.aic_sigma()
- tools.eval_measures.bias()
- tools.eval_measures.bic()
- tools.eval_measures.bic_sigma()
- tools.eval_measures.hqic()
- tools.eval_measures.hqic_sigma()
- tools.eval_measures.iqr()
- tools.eval_measures.maxabs()
- tools.eval_measures.meanabs()
- tools.eval_measures.medianabs()
- tools.eval_measures.medianbias()
- tools.eval_measures.mse()
- tools.eval_measures.rmse()
- tools.eval_measures.stde()
- tools.eval_measures.vare()
- tools.numdiff.approx_fprime()
- tools.numdiff.approx_fprime_cs()
- tools.numdiff.approx_hess1()
- tools.numdiff.approx_hess2()
- tools.numdiff.approx_hess3()
- tools.numdiff.approx_hess_cs()
- tools.tools.add_constant()
- tools.tools.categorical()
- tools.tools.clean0()
- tools.tools.fullrank()
- tools.tools.isestimable()
- tools.tools.recipr()
- tools.tools.recipr0()
- tools.tools.unsqueeze()

首页 API Docs 工具

statsmodels / 0.9.0 / examples / notebooks /

Files

File Name
generated/

Name	Statsmodels
Version
Badge
Last Updated	2018-11-04T23:41:12Z

Docs4dev^®

如果你在使用过程中遇到任何问题，可以在这里提issue。

蜀ICP备14021783号-6

Copyright © Docs4dev all right reserved, powered by Docs4dev