Statistical package in Python based on Pandas
Multiple hypothesis testing in Python
The Scott-Knott Effect Size Difference (ESD) test
Python package for permutation tests, for statistics and machine learning.
Design of single- and multi-stage multi-arm clinical trials
A statistics package with a variety of bootstrap and other resampling tools
Adjust p-values for multiple comparisons
Romano-Wolf p-value adjustments for multiple hypotheses testing via the wild bootstrap for objects of type fixest and fixest_multi from the fixest package
python package for generating compact letter display, summarizing results of posthoc comparison tests after ANOVA
SimTOST is an R package designed to facilitate the sample size estimation for bioequivalence studies using a simulation-based approach.
SimOutUtils - Utilities for analyzing time series simulation output
AskoR pipeline: analysis of gene expression data, using edgeR.
Spatial Inference for Tractometry
A statistics package with a variety of bootstrap and other resampling tools. This repository is synced to the same-named repository owned by GNU-Octave. It exists to facilitate publication of the developmental version of the statistics-resampling toolbox at MathWorks FileExchange.
Statistical testing framework using Monte Carlo simulations.
Dependency-free statistical checks for AI eval claims: multiple-comparisons correction, LLM-judge bias tests, and leave-one-out fragility. Run them before you publish.
A falsification-first quant research project: a confirmed multi-asset TSMOM core, then four overlays (crash-defense, vol-breakout, seasonality, yield-curve regime) and a cross-sectional momentum (XSMOM) counterpart — all systematically tested and honestly rejected, each with a mechanism. Paired-bootstrap + BH-FDR throughout.
R package for sign-flip permutation inference on group fMRI, reporting FWER-corrected p-values. Offers a quantum amplitude-estimation estimator (emulated in R, with an optional real Qiskit backend) next to the classical permutation test.
Simulation studies of power and Type I error of mass univariate statistics for ERP data
This code was written and used for statistical analysis and visualisation of data included in Drube et al. 2021.
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