some new features

.venv/lib/python3.12/site-packages/statsmodels-0.14.3.dist-info/INSTALLER

@@ -0,0 +1 @@
+pip

.venv/lib/python3.12/site-packages/statsmodels-0.14.3.dist-info/LICENSE.txt

@@ -0,0 +1,34 @@
+Copyright (C) 2006, Jonathan E. Taylor
+All rights reserved.
+
+Copyright (c) 2006-2008 Scipy Developers.
+All rights reserved.
+
+Copyright (c) 2009-2018 statsmodels Developers.
+All rights reserved.
+
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+  a. Redistributions of source code must retain the above copyright notice,
+     this list of conditions and the following disclaimer.
+  b. Redistributions in binary form must reproduce the above copyright
+     notice, this list of conditions and the following disclaimer in the
+     documentation and/or other materials provided with the distribution.
+  c. Neither the name of statsmodels nor the names of its contributors
+     may be used to endorse or promote products derived from this software
+     without specific prior written permission.
+
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ARE DISCLAIMED. IN NO EVENT SHALL STATSMODELS OR CONTRIBUTORS BE LIABLE FOR
+ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
+OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH
+DAMAGE.

.venv/lib/python3.12/site-packages/statsmodels-0.14.3.dist-info/METADATA

@@ -0,0 +1,268 @@
+Metadata-Version: 2.1
+Name: statsmodels
+Version: 0.14.3
+Summary: Statistical computations and models for Python
+Home-page: https://www.statsmodels.org/
+Download-URL: 
+Maintainer: statsmodels Developers
+Maintainer-email: pystatsmodels@googlegroups.com
+License: BSD License
+Project-URL: Bug Tracker, https://github.com/statsmodels/statsmodels/issues
+Project-URL: Documentation, https://www.statsmodels.org/stable/index.html
+Project-URL: Source Code, https://github.com/statsmodels/statsmodels
+Platform: any
+Classifier: Development Status :: 4 - Beta
+Classifier: Environment :: Console
+Classifier: Programming Language :: Cython
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+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: License :: OSI Approved :: BSD License
+Classifier: Topic :: Office/Business :: Financial
+Classifier: Topic :: Scientific/Engineering
+Requires-Python: >=3.9
+License-File: LICENSE.txt
+Requires-Dist: numpy <3,>=1.22.3
+Requires-Dist: scipy !=1.9.2,>=1.8
+Requires-Dist: pandas !=2.1.0,>=1.4
+Requires-Dist: patsy >=0.5.6
+Requires-Dist: packaging >=21.3
+Provides-Extra: build
+Requires-Dist: cython >=3.0.10 ; extra == 'build'
+Provides-Extra: develop
+Requires-Dist: cython >=3.0.10 ; extra == 'develop'
+Requires-Dist: cython <4,>=3.0.10 ; extra == 'develop'
+Requires-Dist: setuptools-scm[toml] ~=8.0 ; extra == 'develop'
+Requires-Dist: matplotlib >=3 ; extra == 'develop'
+Requires-Dist: colorama ; extra == 'develop'
+Requires-Dist: joblib ; extra == 'develop'
+Requires-Dist: pytest <8,>=7.3.0 ; extra == 'develop'
+Requires-Dist: pytest-randomly ; extra == 'develop'
+Requires-Dist: pytest-xdist ; extra == 'develop'
+Requires-Dist: pytest-cov ; extra == 'develop'
+Requires-Dist: flake8 ; extra == 'develop'
+Requires-Dist: isort ; extra == 'develop'
+Requires-Dist: pywinpty ; (os_name == "nt") and extra == 'develop'
+Provides-Extra: docs
+Requires-Dist: sphinx ; extra == 'docs'
+Requires-Dist: nbconvert ; extra == 'docs'
+Requires-Dist: jupyter-client ; extra == 'docs'
+Requires-Dist: ipykernel ; extra == 'docs'
+Requires-Dist: matplotlib ; extra == 'docs'
+Requires-Dist: nbformat ; extra == 'docs'
+Requires-Dist: numpydoc ; extra == 'docs'
+Requires-Dist: pandas-datareader ; extra == 'docs'
+
+.. image:: docs/source/images/statsmodels-logo-v2-horizontal.svg
+  :alt: Statsmodels logo
+
+|PyPI Version| |Conda Version| |License| |Azure CI Build Status|
+|Codecov Coverage| |Coveralls Coverage| |PyPI downloads| |Conda downloads|
+
+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.
+
+.. code:: 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
+
+.. |Azure CI Build Status| image:: https://dev.azure.com/statsmodels/statsmodels-testing/_apis/build/status/statsmodels.statsmodels?branchName=main
+   :target: https://dev.azure.com/statsmodels/statsmodels-testing/_build/latest?definitionId=1&branchName=main
+.. |Codecov Coverage| image:: https://codecov.io/gh/statsmodels/statsmodels/branch/main/graph/badge.svg
+   :target: https://codecov.io/gh/statsmodels/statsmodels
+.. |Coveralls Coverage| image:: https://coveralls.io/repos/github/statsmodels/statsmodels/badge.svg?branch=main
+   :target: https://coveralls.io/github/statsmodels/statsmodels?branch=main
+.. |PyPI downloads| image:: https://img.shields.io/pypi/dm/statsmodels?label=PyPI%20Downloads
+   :alt: PyPI - Downloads
+   :target: https://pypi.org/project/statsmodels/
+.. |Conda downloads| image:: https://img.shields.io/conda/dn/conda-forge/statsmodels.svg?label=Conda%20downloads
+   :target: https://anaconda.org/conda-forge/statsmodels/
+.. |PyPI Version| image:: https://img.shields.io/pypi/v/statsmodels.svg
+   :target: https://pypi.org/project/statsmodels/
+.. |Conda Version| image:: https://anaconda.org/conda-forge/statsmodels/badges/version.svg
+   :target: https://anaconda.org/conda-forge/statsmodels/
+.. |License| image:: https://img.shields.io/pypi/l/statsmodels.svg
+   :target: https://github.com/statsmodels/statsmodels/blob/main/LICENSE.txt

.venv/lib/python3.12/site-packages/statsmodels-0.14.3.dist-info/WHEEL

@@ -0,0 +1,6 @@
+Wheel-Version: 1.0
+Generator: setuptools (75.0.0)
+Root-Is-Purelib: false
+Tag: cp312-cp312-manylinux_2_17_x86_64
+Tag: cp312-cp312-manylinux2014_x86_64
+

.venv/lib/python3.12/site-packages/statsmodels-0.14.3.dist-info/top_level.txt

@@ -0,0 +1 @@
+statsmodels