py311-statsmodels

Complement to SciPy for statistical computations

statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics and estimation and inference for statistical models. Main Features: - Linear regression models - Mixed Linear Model with mixed effects and variance components - GLM: Generalized linear models with support for all of the one-parameter exponential family distributions - Bayesian Mixed GLM for Binomial and Poisson - GEE: Generalized Estimating Equations for one-way clustered or longitudinal data - Discrete models - RLM: Robust linear models with support for several M-estimators. - Time Series Analysis: models for time series analysis - Survival analysis - Multivariate - Nonparametric statistics: Univariate and multivariate kernel density estimators - Datasets: Datasets used for examples and in testing - Statistics: a wide range of statistical tests - Imputation with MICE, regression on order statistic and Gaussian imputation - Mediation analysis - Graphics includes plot functions for visual analysis of data and model results - I/O - Miscellaneous models - Sandbox: statsmodels contains a sandbox folder with code in various stages of development and testing which is not considered "production ready". This covers among others