Statsmodels: statistical modeling and econometrics in Python

A light-weight, flexible, and expressive statistical data testing library

Statistical Inference for Data Science: UBC Term Project (2022W) - Inferential Analysis

Reproducibility code for Robust Kernel Hypothesis Testing under Data Corruption, by Schrab and Kim

dckernel package implementing dcMMD and dcHSIC from Robust Kernel Hypothesis Testing under Data Corruption, by Schrab and Kim

Reproducibility code for Efficient Aggregated Kernel Tests using Incomplete U-statistics, by Schrab, Kim, Guedj and Gretton: https://arxiv.org/abs/2206.09194 NeurIPS 2022

KSDAgg package implementing the KSDAgg test proposed in KSD Aggregated Goodness-of-fit Test by Schrab, Guedj and Gretton: https://arxiv.org/abs/2202.00824 NeurIPS 2022

AggInc package implementing the MMDAggInc, HSICAggInc and KSDAggInc tests proposed in Efficient Aggregated Kernel Tests using Incomplete U-statistics by Schrab, Kim, Guedj and Gretton: https://arxiv.org/abs/2206.09194 NeurIPS 2022

Reproducibility code for MMD Aggregated Two-Sample Test, by Schrab, Kim, Albert, Laurent, Guedj and Gretton: https://arxiv.org/abs/2110.15073

Reproducibility code for Differentially Private Permutation Tests: Applications to Kernel Methods, by Kim and Schrab

Reproducibility code for MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting, by Biggs, Schrab, and Gretton: https://arxiv.org/abs/2306.08777

MMD-FUSE package implementing the MMD-FUSE test proposed in MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting by Biggs, Schrab, and Gretton: https://arxiv.org/abs/2306.08777

MMDAgg package implementing the MMDAgg test proposed in MMD Aggregated Two-Sample Test by Schrab, Kim, Albert, Laurent, Guedj and Gretton: https://arxiv.org/abs/2110.15073

Code for reproducible experiments presented in KSD Aggregated Goodness-of-fit Test. https://arxiv.org/abs/2202.00824 NeurIPS 2022

dpkernel package implementing dpMMD and dpHSIC from Differentially Private Permutation Tests: Applications to Kernel Methods, by Kim and Schrab

Differential Expression Analysis tool box R lang package for omics data

Welcome to the repository for the Indian Startup Funding Analysis project. This data analysis project was commissioned by a newly funded Indian startup. Our primary goal is to provide valuable insights and actionable recommendations that will help optimize fund allocation, enhance operational efficiency, and drive sustainable growth.

Python package for multivariate hypothesis testing

This Repo contains tools that allow us to import, clean, manipulate, and visualize data —Includes Python libraries, like pandas, NumPy, Matplotlib, and many more to work with real-world datasets to learn the statistical and machine learning techniques.