Enhancing `ggplot2` plots with statistical analysis 📊🎨📣

Statistical package in Python based on Pandas

Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"

Learning kernels to maximize the power of MMD tests

Development version of 'spatstat' package ..............................

Testing common random-number generators (RNG)

Monitor the stability of a pandas or spark dataframe ⚙︎

Ruby gem for some statistical operations without any statistical language dependency

NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.

Fast Unit Root Tests and OLS regression in C++ with wrappers for R and Python

Meta.Numerics is library for advanced numerical computing on the .NET platform. It offers an object-oriented API for statistical analysis, advanced functions, Fourier transforms, numerical integration and optimization, and matrix algebra.

NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.

Improved version of the NIST Statistical Test Suite (STS)

Python port of "Common statistical tests are linear models" by Jonas Kristoffer Lindeløv.

Parametric and non-parametric statistical tests

Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.

Statistical inference on machine learning or general non-parametric models

Hypothesis and statistical testing in Python

Jupyter notebooks with examples of statistical methods and analyses using R.

Statistical Tests for Algorithms Comparison (STAC) is a new platform for statistical analysis to verify the results obtained from computational intelligence algorithms.

Implicit generative models and related stuff based on the MMD, in PyTorch

ICML 2017. Kernel-based adaptive linear-time independence test.

The Scott-Knott Effect Size Difference (ESD) test

Confound-isolating cross-validation approach to control for a confounding effect in a predictive model.

[PNAS2018] Recurrent computations for visual pattern completion: Classification of occluded images in humans and recurrent neural networks

Unofficial mirror of TestU01, a test suite for random number generator (C library) for the empirical statistical testing of uniform random number generators

Permutation algorithms to test statistical significance of experimental results.

Machine learning library for classification tasks

Linear Regression Analysis on Wine data - Pre-processing data, Exploratory Data Analysis, Building a model, Check assumptions, Goodness of fit and Compare with different methods.

Set of functions to semi-automatically build and test Ordinary Least Squares (OLS) models in R in parallel.