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开发者页面 Statsmodels 0 14 4 Statsmodels 文档

Leo Migdal
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开发者页面 statsmodels 0 14 4 statsmodels 文档

本页解释如何通过提交补丁、统计测试、新模型或示例来为 statsmodels 的开发做出贡献。 statsmodels 在 Github 上使用 Git 版本控制系统进行开发。 指定使用的 statsmodels 版本。您可以使用 sm.version.full_version 来完成此操作 如果问题似乎涉及其他依赖项，还包括 sm.show_versions() 的输出 首先，查看 使用 statsmodels 代码 部分以了解 Git 版本控制系统的介绍。 statsmodels is using github to store the updated documentation.

Two version are available: Development, the latest build of the main branch API stability is not guaranteed for new features, although even in this case changes will be made in a backwards compatible way if possible. The stability of a new feature depends on how much time it was already in statsmodels main and how much usage it has already seen. If there are specific known problems or limitations, then they are mentioned in the docstrings. This release bring official Pyodide support to a statsmodel release.

It is otherwise identical to the previous release. Special thanks to Agriya Khetarpal for working through Pyodide-specific issues, and improving other areas of statsmodels while doing so. statsmodels 是一个 Python 模块，提供用于估计各种统计模型的类和函数，以及用于进行统计检验和统计数据探索的类和函数。每个估计器都提供广泛的统计结果列表。结果经过测试，与现有的统计包进行比较，以确保其正确性。该包是在开源的 Modified BSD (3-clause) 许可下发布的。在线文档托管在 statsmodels.org。 statsmodels 支持使用 R 风格公式和 pandas DataFrame 来指定模型。以下是一个使用普通最小二乘法的简单示例 查看 dir(results) 以查看可用的结果。属性在 results.__doc__ 中描述，结果方法有自己的文档字符串。 Seabold, Skipper 和 Josef Perktold。 "statsmodels：Python 的计量经济学和统计建模。” 第九届 Python in Science 大会论文集。 2010 年。

statsmodels is using github to store the updated documentation. Two version are available: Development, the latest build of the main branch API stability is not guaranteed for new features, although even in this case changes will be made in a backwards compatible way if possible. The stability of a new feature depends on how much time it was already in statsmodels main and how much usage it has already seen. If there are specific known problems or limitations, then they are mentioned in the docstrings.

TreatmentEffect estimates treatment effect for a binary treatment and potential outcome for a continuous outcome variable using 5 different methods, ipw, ra, aipw, aipw-wls, ipw-ra. Standard errors and inference are based on the joint GMM representation of selection or treatment model, outcome model and effect functions. statsmodels.discrete.truncated_model.HurdleCountModel implements hurdle models for count data with either Poisson or NegativeBinomialP as submodels. Three left truncated models used for zero truncation are available, statsmodels.discrete.truncated_model.TruncatedLFPoisson, statsmodels.discrete.truncated_model.TruncatedLFNegativeBinomialP and statsmodels.discrete.truncated_model.TruncatedLFGeneralizedPoisson. Models for right censoring at one are implemented but only as support for the hurdle models. The models module of scipy.stats was originally written by Jonathan Taylor.

For some time it was part of scipy but was later removed. During the Google Summer of Code 2009, statsmodels was corrected, tested, improved and released as a new package. Since then, the statsmodels development team has continued to add new models, plotting tools, and statistical methods. 大多数结果至少在一个其他统计软件包中得到验证：R、Stata 或 SAS。最初重写和持续开发的指导原则是一切数字都必须得到验证。一些统计方法使用蒙特卡罗研究进行测试。虽然我们努力遵循这种测试驱动的方法，但不能保证代码没有错误且始终有效。一些辅助函数测试不足，一些边缘情况可能没有正确考虑，并且许多统计模型中固有的数值问题可能性。我们特别感谢对此类问题的任何帮助和报告，以便我们不断改进现有模型。 现有模型的用户界面基本已稳定，我们预计未来不会出现太多重大变化。对于现有代码，虽然还没有关于 API 稳定性的保证，但我们在除极少数情况外，都有很长的弃用期，并且尽量将需要现有用户调整的更改降至最低。对于较新的模型，我们可能会在获得更多经验和反馈后调整用户界面。这些更改将在我们的文档中发布的发布说明中列出。 如果您遇到错误或意外行为，请在 issue tracker 上报告。使用 show_versions 命令列出 statsmodels 及其依赖项的已安装版本。

Google www.google.com : Google Summer of Code (GSOC) 2009-2017。

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本页解释如何通过提交补丁、统计测试、新模型或示例来为 Statsmodels 的开发做出贡献。 Statsmodels 在 Github 上使用 Git 版本控制系统进行开发。 指定使用的

本页解释如何通过提交补丁、统计测试、新模型或示例来为 statsmodels 的开发做出贡献。 statsmodels 在 Github 上使用 Git 版本控制系统进行开发。 指定使用的 statsmodels 版本。您可以使用 sm.version.full_version 来完成此操作 如果问题似乎涉及其他依赖项，还包括 sm.show_versions() 的输出 首先，查看 使用 statsmodels 代码 部分以了解 Git 版本控制系统的介绍。 statsmodels is using github to store the updated documentation.

Two Version Are Available: Development, The Latest Build Of The

Two version are available: Development, the latest build of the main branch API stability is not guaranteed for new features, although even in this case changes will be made in a backwards compatible way if possible. The stability of a new feature depends on how much time it was already in statsmodels main and how much usage it has already seen. If there are specific known problems or limitations,...

It Is Otherwise Identical To The Previous Release. Special Thanks

It is otherwise identical to the previous release. Special thanks to Agriya Khetarpal for working through Pyodide-specific issues, and improving other areas of statsmodels while doing so. statsmodels 是一个 Python 模块，提供用于估计各种统计模型的类和函数，以及用于进行统计检验和统计数据探索的类和函数。每个估计器都提供广泛的统计结果列表。结果经过测试，与现有的统计包进行比较，以确保其正确性。该包是在开源的 Modified BSD (3-clause) 许可下发布的。在线文档托管在 statsmodels.org。 statsmodels 支持使用 R 风格公式和 pandas Data...

Statsmodels Is Using Github To Store The Updated Documentation. Two

statsmodels is using github to store the updated documentation. Two version are available: Development, the latest build of the main branch API stability is not guaranteed for new features, although even in this case changes will be made in a backwards compatible way if possible. The stability of a new feature depends on how much time it was already in statsmodels main and how much usage it has al...

TreatmentEffect Estimates Treatment Effect For A Binary Treatment And Potential

TreatmentEffect estimates treatment effect for a binary treatment and potential outcome for a continuous outcome variable using 5 different methods, ipw, ra, aipw, aipw-wls, ipw-ra. Standard errors and inference are based on the joint GMM representation of selection or treatment model, outcome model and effect functions. statsmodels.discrete.truncated_model.HurdleCountModel implements hurdle model...