Metadata-Version: 2.4
Name: statsmodels
Version: 0.15.0
Summary: Statistical computations and models for Python
Keywords: statistics,econometrics,time series,regression,anova,statistical tests,linear models,generalized linear models,discrete choice models,robust linear models,mixed linear models,time series analysis,state space models,vector autoregression,volatility modeling,unit root tests,cointegration tests,nonparametric methods,multivariate statistics
Maintainer-Email: statsmodels Developers <pystatsmodels@googlegroups.com>
License-Expression: BSD-3-Clause
License-File: LICENSE.txt
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Topic :: Office/Business :: Financial
Classifier: Topic :: Scientific/Engineering
Project-URL: homepage, https://www.statsmodels.org
Project-URL: documentation, https://www.statsmodels.org/stable/index.html
Project-URL: repository, https://github.com/statsmodels/statsmodels
Project-URL: changelog, https://bashtage.github.io/arch/changes.html
Project-URL: bugtracker, https://github.com/statsmodels/statsmodels/issues
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Description-Content-Type: text/markdown

![Statsmodels logo](docs/source/images/statsmodels-logo-v2-horizontal.svg)

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# About statsmodels

statsmodels is a Python package that provides a complement to scipy for
statistical computations including descriptive statistics and estimation
and inference for statistical models.

# Documentation

The documentation for the latest release is at

<https://www.statsmodels.org/stable/>

The documentation for the development version is at

<https://www.statsmodels.org/dev/>

Recent improvements are highlighted in the release notes

<https://www.statsmodels.org/stable/release/>

Backups of documentation are available at
<https://statsmodels.github.io/stable/> and
<https://statsmodels.github.io/dev/>.

# Main Features

- Linear regression models:
  - Ordinary least squares
  - Generalized least squares
  - Weighted least squares
  - Least squares with autoregressive errors
  - Quantile regression
  - Recursive least squares
- 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:
  - Logit and Probit
  - Multinomial logit (MNLogit)
  - Poisson and Generalized Poisson regression
  - Negative Binomial regression
  - Zero-Inflated Count models
- RLM: Robust linear models with support for several M-estimators.
- Time Series Analysis: models for time series analysis
  - Complete StateSpace modeling framework
    - Seasonal ARIMA and ARIMAX models
    - VARMA and VARMAX models
    - Dynamic Factor models
    - Unobserved Component models
  - Markov switching models (MSAR), also known as Hidden Markov Models
    (HMM)
  - Univariate time series analysis: AR, ARIMA
  - Vector autoregressive models, VAR and structural VAR
  - Vector error correction model, VECM
  - exponential smoothing, Holt-Winters
  - Hypothesis tests for time series: unit root, cointegration and
    others
  - Descriptive statistics and process models for time series analysis
- Survival analysis:
  - Proportional hazards regression (Cox models)
  - Survivor function estimation (Kaplan-Meier)
  - Cumulative incidence function estimation
- Multivariate:
  - Principal Component Analysis with missing data
  - Factor Analysis with rotation
  - MANOVA
  - Canonical Correlation
- Nonparametric statistics: Univariate and multivariate kernel density
  estimators
- Datasets: Datasets used for examples and in testing
- Statistics: a wide range of statistical tests
  - diagnostics and specification tests
  - goodness-of-fit and normality tests
  - functions for multiple testing
  - various additional 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
  - Tools for reading Stata .dta files, but pandas has a more recent
    version
  - Table output to ascii, latex, and html
- 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
  - Generalized method of moments (GMM) estimators
  - Kernel regression
  - Various extensions to scipy.stats.distributions
  - Panel data models
  - Information theoretic measures

# How to get it

The main branch on GitHub is the most up to date code

<https://www.github.com/statsmodels/statsmodels>

Source download of release tags are available on GitHub

<https://github.com/statsmodels/statsmodels/tags>

Binaries and source distributions are available from PyPi

<https://pypi.org/project/statsmodels/>

Binaries can be installed in Anaconda

conda install statsmodels

# Getting the latest code

## Installing the most recent nightly wheel

The most recent nightly wheel can be installed using pip.

``` bash
python -m pip install -i https://pypi.anaconda.org/scientific-python-nightly-wheels/simple statsmodels --upgrade --use-deprecated=legacy-resolver
```

## Installing from sources

See INSTALL.txt for requirements or see the documentation

<https://statsmodels.github.io/dev/install.html>

# Contributing

Contributions in any form are welcome, including:

- Documentation improvements
- Additional tests
- New features to existing models
- New models

<https://www.statsmodels.org/stable/dev/test_notes>

for instructions on installing statsmodels in *editable* mode.

# License

Modified BSD (3-clause)

# Discussion and Development

Discussions take place on the mailing list

<https://groups.google.com/group/pystatsmodels>

and in the issue tracker. We are very interested in feedback about
usability and suggestions for improvements.

# Bug Reports

Bug reports can be submitted to the issue tracker at

<https://github.com/statsmodels/statsmodels/issues>