betaDelta: Confidence Intervals for Standardized Regression Coefficients

betaMC: Generates Monte Carlo confidence intervals for standardized regression coefficients for models fitted by lm().

betaSandwich: Robust Confidence Intervals for Standardized Regression Coefficients

betaNB: Generates nonparametric bootstrap confidence intervals for standardized regression coefficients and other effect sizes for models fitted by lm().

semmcci: Monte Carlo Confidence Intervals in Structural Equation Modeling

A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.

Shiny app illustrating one interpretation of confidence intervals

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.

A statistics package with a variety of bootstrap and other resampling tools

📊 Computation and processing of models' parameters

Bringing back uncertainty to machine learning.

Sub-package of spatstat containing functionality for parametric modelling and inference

Basic bootstrapping for estimation statistics.

This repository contains exercises on statistical analysis and probability calculations. Each question is answered with detailed explanations, covering topics like data types, probability distributions, expected values, descriptive statistics, skewness, kurtosis, confidence intervals, & hypothesis test

A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.

Sub-package of spatstat providing functions for exploratory and nonparametric data analysis

Find the likelihood based confidence intervals for parameters in structural equation modeling

One Sample Test

An R-Package to estimate and plot confounder-adjusted survival curves (single event survival data) and confounder-adjusted cumulative incidence functions (data with competing risks) using various methods.

Randomization-based inference in Python