Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
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Updated
Oct 16, 2026 - HTML
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
Randomization-based inference in Python
MLstatkit is a comprehensive Python library designed to seamlessly integrate established statistical methods into machine learning projects.
Python package for permutation tests, for statistics and machine learning.
A MATLAB package for multivariate permutation testing and effect size measurement
An R/Bioconfuctor package for association analysis of genomic regions based on permutation tests
A statistics package with a variety of bootstrap and other resampling tools
Machine learning tools for the analysis of systems serology data
Topological Learning for Brain Networks (Annals of Applied Statistics; MICCAI 2021)
Statistical package for fast exact tests and simulations
Tools for analyzing and quantifying effects of confounder variables on machine learning model predictions.
'R6'-Based Flexible Framework for Permutation Tests
Power Outage Data Analysis in USA
Python package for mechanistic interpretability providing statistical audits of activation patching for TransformerLens with False Discovery Rate (FDR) control, Benjamini-Hochberg correction, and sign-flip p-values.
Is your backtest real? Deflated Sharpe Ratio, backtest-overfitting (PBO) and lookahead checks with measured false-positive rates. Works with vectorbt, backtesting.py and TradingView.
Permutation tests for MixedModels.jl
Permutation-Based FDR Point and Confidence Interval Estimation
Mathematical and statistical applications for HP Prime.
Easy-to-use collection of statistical methods and techniques, all written in R 🗂
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