gala-anteater src a0dddf02cdaebfe8c414e9c4b2b12b1b94214ae8888dff36d37e492b9afbdd67 A time-series anomaly detection platform for operating system. Abnormal detection module for A-Ops project https://gitee.com/openeuler/gala-anteater gala-anteater x86_64 92e630bc2a3b0948e901b98e94e37510401be86200d5ec44efcfefaccb8fada4 A time-series anomaly detection platform for operating system. Abnormal detection module for A-Ops project https://gitee.com/openeuler/gala-anteater gala-inference x86_64 9b8805fcec34d05960851e589129d66f2de00e83dcbf3bfcb435f85e7a3ac91a Cause inference module for gala-ops project Cause inference module for A-Ops project https://gitee.com/openeuler/gala-spider gala-ops x86_64 df8db3fa144b27e85d20b75c4b9de67cd1fe26623b4d312341cbfe3dda53fadf gala-anteater/spider/inference installation package This package requires gala-anteater/spider/inference, allowing users to install them all at once https://gitee.com/openeuler/gala-spider gala-spider src 26a2a810cd3dc9670b833aa886fad582e0e0a1c15d497381cf43a68717254e7e OS topological graph storage service and cause inference service for gala-ops project OS topological graph storage service for gala-ops project https://gitee.com/openeuler/gala-spider gala-spider x86_64 598d4bc7c780635d0a2a5a569921db8c424cdb1a387a2e53bd87c7a0147ff98f OS topological graph storage service and cause inference service for gala-ops project OS topological graph storage service for gala-ops project https://gitee.com/openeuler/gala-spider python-pingouin src acfdc41bb94e6b9275979634524e0645716be1142a54a42734ea01c3534a9c2e Pingouin: statistical package for Python **Pingouin** is an open-source statistical package written in Python 3 and based mostly on Pandas and NumPy. Some of its main features are listed below. For a full list of available functions, please refer to the `API documentation <https://pingouin-stats.org/build/html/api.html#>`_. 1. ANOVAs: N-ways, repeated measures, mixed, ancova 2. Pairwise post-hocs tests (parametric and non-parametric) and pairwise correlations 3. Robust, partial, distance and repeated measures correlations 4. Linear/logistic regression and mediation analysis 5. Bayes Factors 6. Multivariate tests 7. Reliability and consistency 8. Effect sizes and power analysis 9. Parametric/bootstrapped confidence intervals around an effect size or a correlation coefficient 10. Circular statistics 11. Chi-squared tests 12. Plotting: Bland-Altman plot, Q-Q plot, paired plot, robust correlation... Pingouin is designed for users who want **simple yet exhaustive statistical functions**. For example, the :code:`ttest_ind` function of SciPy returns only the T-value and the p-value. By contrast, the :code:`ttest` function of Pingouin returns the T-value, the p-value, the degrees of freedom, the effect size (Cohen's d), the 95% confidence intervals of the difference in means, the statistical power and the Bayes Factor (BF10) of the test. https://pingouin-stats.org/index.html python-pingouin-help noarch 8ddf2c7f5caf01975cc0b3fc174ed3e79be3a00474f44b45497974e30343f6a0 Development documents and examples for pingouin **Pingouin** is an open-source statistical package written in Python 3 and based mostly on Pandas and NumPy. Some of its main features are listed below. For a full list of available functions, please refer to the `API documentation <https://pingouin-stats.org/build/html/api.html#>`_. 1. ANOVAs: N-ways, repeated measures, mixed, ancova 2. Pairwise post-hocs tests (parametric and non-parametric) and pairwise correlations 3. Robust, partial, distance and repeated measures correlations 4. Linear/logistic regression and mediation analysis 5. Bayes Factors 6. Multivariate tests 7. Reliability and consistency 8. Effect sizes and power analysis 9. Parametric/bootstrapped confidence intervals around an effect size or a correlation coefficient 10. Circular statistics 11. Chi-squared tests 12. Plotting: Bland-Altman plot, Q-Q plot, paired plot, robust correlation... Pingouin is designed for users who want **simple yet exhaustive statistical functions**. For example, the :code:`ttest_ind` function of SciPy returns only the T-value and the p-value. By contrast, the :code:`ttest` function of Pingouin returns the T-value, the p-value, the degrees of freedom, the effect size (Cohen's d), the 95% confidence intervals of the difference in means, the statistical power and the Bayes Factor (BF10) of the test. https://pingouin-stats.org/index.html python3-gala-anteater x86_64 42f04c2d183da18b4fd7d21e5fd556c4ae89ac10716543e47d27ac64a588faa8 Python3 package of gala-anteater Python3 package of gala-anteater https://gitee.com/openeuler/gala-anteater python3-gala-inference x86_64 e79e671b485a6d43d2a24c511afbadb14c83828ae58ab6e223de7618f13dadd5 Python3 package of gala-inference Python3 package of gala-inference https://gitee.com/openeuler/gala-spider python3-gala-spider x86_64 7c66f612c0b3aa1bf5f8fdbec7a759fa84f85fdaeaed78eeca60c5732050a6af Python3 package of gala-spider Python3 package of gala-spider https://gitee.com/openeuler/gala-spider python3-pingouin noarch 8eb521b1182f49075aa03f70698ea8c63220e1756cdf79c4683280223c7aef51 Pingouin: statistical package for Python **Pingouin** is an open-source statistical package written in Python 3 and based mostly on Pandas and NumPy. Some of its main features are listed below. For a full list of available functions, please refer to the `API documentation <https://pingouin-stats.org/build/html/api.html#>`_. 1. ANOVAs: N-ways, repeated measures, mixed, ancova 2. Pairwise post-hocs tests (parametric and non-parametric) and pairwise correlations 3. Robust, partial, distance and repeated measures correlations 4. Linear/logistic regression and mediation analysis 5. Bayes Factors 6. Multivariate tests 7. Reliability and consistency 8. Effect sizes and power analysis 9. Parametric/bootstrapped confidence intervals around an effect size or a correlation coefficient 10. Circular statistics 11. Chi-squared tests 12. Plotting: Bland-Altman plot, Q-Q plot, paired plot, robust correlation... Pingouin is designed for users who want **simple yet exhaustive statistical functions**. For example, the :code:`ttest_ind` function of SciPy returns only the T-value and the p-value. By contrast, the :code:`ttest` function of Pingouin returns the T-value, the p-value, the degrees of freedom, the effect size (Cohen's d), the 95% confidence intervals of the difference in means, the statistical power and the Bayes Factor (BF10) of the test. https://pingouin-stats.org/index.html