Statsmodels Main Website Source Github

There was an error while loading. Please reload this page. There was an error while loading. Please reload this page. Statsmodels: statistical modeling and econometrics in Python documentation for statsmodels - currently temporary structure and location

There was an error while loading. Please reload this page. Statsmodels: statistical modeling and econometrics in Python store for csv files used in examples that are not included in statsmodels.datasets statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics and estimation and inference for statistical models. The documentation for the latest release is at

The documentation for the development version is at Recent improvements are highlighted in the release notes https://www.statsmodels.org/stable/release/ There was an error while loading. Please reload this page. pip install statsmodels Copy PIP instructions

Statistical computations and models for Python statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics and estimation and inference for statistical models. The documentation for the latest release is at The documentation for the development version is at statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator.

The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. The online documentation is hosted at statsmodels.org. statsmodels supports specifying models using R-style formulas and pandas DataFrames. Here is a simple example using ordinary least squares: You can also use numpy arrays instead of formulas:

Have a look at dir(results) to see available results. Attributes are described in results.__doc__ and results methods have their own docstrings. Please use following citation to cite statsmodels in scientific publications: statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct.

The package is released under the open source Modified BSD (3-clause) license. The online documentation is hosted at statsmodels.org. statsmodels supports specifying models using R-style formulas and pandas DataFrames. Here is a simple example using ordinary least squares: You can also use numpy arrays instead of formulas: Have a look at dir(results) to see available results.

Attributes are described in results.__doc__ and results methods have their own docstrings. Please use following citation to cite statsmodels in scientific publications: statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license.

The online documentation is hosted at statsmodels.org. Since version 0.5.0 of statsmodels, you can use R-style formulas together with pandas data frames to fit your models. Here is a simple example using ordinary least squares: You can also use numpy arrays instead of formulas: Have a look at dir(results) to see available results. Attributes are described in results.__doc__ and results methods have their own docstrings.

When using statsmodels in scientific publication, please consider using the following citation:

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