gala-anteater aarch64 3ea4494255a4ef3589fbd20a198ec7b757d0cbf997b6f45ac1984c51b1c16bb2 A time-series anomaly detection platform for operating system. Abnormal detection module for A-Ops project https://gitee.com/openeuler/gala-anteater gala-anteater src 26a8cf437bff4b42347ad5ed2e8659994d78927de8d7fc5e736c1693411c84cc A time-series anomaly detection platform for operating system. Abnormal detection module for A-Ops project https://gitee.com/openeuler/gala-anteater gala-inference aarch64 e23df573d53ce119cc928907923d040fa09d10cc222844c33e8c4672e1d325fc Cause inference module for gala-ops project Cause inference module for A-Ops project https://gitee.com/openeuler/gala-spider gala-ops aarch64 a9fe7f150e479bb58ad56e7401278826b68b7adedf3ef397c4288ac56ed2f8a5 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 aarch64 31a09de1894368451c838f6ab39b2ba5a3839c94cd59744865c99f898c7abb49 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 src 5a449ecae1eb390e3f69bf3e1e8b62bd2dfb5aa63c02233fddce1d15e3fa6b16 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 4ad59baa784600ebf167b42c5881085cd96dbba5e5f32d8a86abeb0cb3e52c87 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 c01ecc66791c60f17eb804d409ac9b622b56579bbd7d18e87550b33b7fb78bb0 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 aarch64 45b2eb4989530f61d1c29e78e1eab45a36800daf55004ea82a456084854ba86a Python3 package of gala-anteater Python3 package of gala-anteater https://gitee.com/openeuler/gala-anteater python3-gala-inference aarch64 21c197e07537c823773f919d77afe47d6ddf7a030558d287b4f617e55e7867a7 Python3 package of gala-inference Python3 package of gala-inference https://gitee.com/openeuler/gala-spider python3-gala-spider aarch64 feeff9d04247ca74ed1d026f507168037108c5f060d89d58c9eb080c460af801 Python3 package of gala-spider Python3 package of gala-spider https://gitee.com/openeuler/gala-spider python3-pingouin noarch 9343aad55abcff0207591c135ff3f137a9820e01fa7ef658a092d6088891a4ad 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