This paper develops new methods to handle false positives in High-Throughput Screening experiments.
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Updated
Sep 14, 2018
This paper develops new methods to handle false positives in High-Throughput Screening experiments.
R package MHTmult: Multiple Hypotheses Testing for Multiple Families Structure
FDR-controlling multiple testing procedure with n screening stages for hypothesis with a family structure.
Exploring the utility of surface approximation using non-radial basis functions.
Python notebook on GtSt testing procedures on the LARS path. Code associated with the manuscript "Multiple Testing and Variable Selection along Least Angle Regression's path" (J.-M. Azaïs & Y. De Castro)
This repository contains a collection of functions to evaluate investment strategies regarding multiple testing concerns.
Causal Inference for Genomic Data with Multiple Heterogeneous Outcomes
MSc Thesis dissertation, results (rendered HTML) in https://gmiliarakis.github.io
A FDR controlling procedure based on hidden Markov random field (Biometrics-15 paper)
NYU DS-GA 1020 Final Project
Fixed Sequence Multiple Testing Procedures
🚩 Uncertainty-Quantified (Conformal) Anomaly Detection for PyOD.
Progressive permutation for a dynamic representation of the robustness of microbiome discoveries
Repository for R and Python packages and reproduction codes in Weighted Conformalized Selection paper
A Shiny app for graphical multiplicity control
POSSA: Power simulation for sequential analyses and multiple hypotheses.
Solutions of applied exercises contained in "An Introduction to Statistical Learning with Applications in Python", by Tibshirani et al, edition 2023
The MultipleTesting package offers common algorithms for p-value adjustment and combination and more…
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