gala-anteater src 63c5824e11bba8f8edc7cf9a149a4e8869487b85e4a2877cc14736c92c5e6313 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 4f95004e4a0d0d6635b1c90cf580b9f402567d9481a3ff85071683b802e676b8 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 027eef35bb16f90feaf2f9e2c69476e7fe8096fa4ae31143c2848e6fd9b92600 Cause inference module for gala-ops project Cause inference module for A-Ops project https://gitee.com/openeuler/gala-spider gala-ops x86_64 11b9a3301a1ea93bef13abed9ebc76d25063dbc95e30ed5ca0a6e5297d305b95 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 3afd7a3b554bc547a8575177c41ad0efab6ba8148cdba7fb5b7a24e3c159070a 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 78beb18ee6cef01a77042e1b482d6fdadb3f6990d2a917e0d8d4deb62aba80a3 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 16517fd6db2e247a7bd96597f646b65829547bcc6d0425b2cddb05db998add0f 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 7911df7a5d39f3430b973a4f0d2ea9679247ac88b6054e140252aa98dec6e83d 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 458fa3a6c89d5138a0c2c3a5c01218b5603b8a5b737553fecf0556931b54a761 Python3 package of gala-anteater Python3 package of gala-anteater https://gitee.com/openeuler/gala-anteater python3-gala-inference x86_64 aa46c37aeadfe74a2a21807b383c88d0175f0e20550c28b339373ff83a7d5a14 Python3 package of gala-inference Python3 package of gala-inference https://gitee.com/openeuler/gala-spider python3-gala-spider x86_64 856315c8117d2bc80ed2b9897e7f1b097848054e530d1c50763fbb60028c4f1d Python3 package of gala-spider Python3 package of gala-spider https://gitee.com/openeuler/gala-spider python3-pingouin noarch 0597dd430843438933404276aeb06b0c662d19a160f8476ad3eb506f66acf272 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