Statsmodels: statistical modeling and econometrics in Python
A light-weight, flexible, and expressive statistical data testing library
Enabling easy statistical significance testing for deep neural networks.
Python package for multivariate hypothesis testing
Learning kernels to maximize the power of MMD tests
Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python
Multiple hypothesis testing in Python
Hypothesis and statistical testing in Python
Robust statistics in Python
This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
Grammars suitable for lark parser and Hypothesis
AB test calculator run through Streamlit
A Modern Python Package Template
Critical difference diagrams with Python and Tikz
Causal inference, differential expression, and co-expression for scRNA-seq
Significance tests of feature relevance for a black-box learner
AB test sample size calculator run through Streamlit
pMoSS (p-value Model using the Sample Size) is a Python code to model the p-value as an n-dependent function using Monte Carlo cross-validation. Exploits the dependence on the sample size to characterize the differences among groups of large datasets
Python tools for working with the IceCube public data.
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