python -m pip install -i statsmodels -upgrade -use-deprecated =legacy-resolver Installing from sources

The most recent nightly wheel can be installed using pip. Source download of release tags are available on GitHubīinaries and source distributions are available from PyPiĬonda install statsmodels Getting the latest code Installing the most recent nightly wheel The main branch on GitHub is the most up to date code Generalized method of moments (GMM) estimators Sandbox: statsmodels contains a sandbox folder with code in various stages ofĭevelopment and testing which is not considered “production ready”. dta files, but pandas has a more recent version Graphics includes plot functions for visual analysis of data and model results Imputation with MICE, regression on order statistic and Gaussian imputation Statistics: a wide range of statistical tests Nonparametric statistics: Univariate and multivariate kernel density estimatorsĭatasets: Datasets used for examples and in testing Principal Component Analysis with missing data Survivor function estimation (Kaplan-Meier) Proportional hazards regression (Cox models) Hypothesis tests for time series: unit root, cointegration and othersĭescriptive statistics and process models for time series analysis Vector autoregressive models, VAR and structural VAR Univariate time series analysis: AR, ARIMA Markov switching models (MSAR), also known as Hidden Markov Models (HMM) Time Series Analysis: models for time series analysis RLM: Robust linear models with support for several M-estimators. Poisson and Generalized Poisson regression GEE: Generalized Estimating Equations for one-way clustered or longitudinal data GLM: Generalized linear models with support for all of the one-parameterīayesian Mixed GLM for Binomial and Poisson Mixed Linear Model with mixed effects and variance components Recent improvements are highlighted in the release notesīackups of documentation are available at The documentation for the development version is at The documentation for the latest release is at

Statistical computations including descriptive statistics and estimationĪnd inference for statistical models. Statsmodels is a Python package that provides a complement to scipy for

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