Calculating robust effect sizes using bootstrap (resampling) technique in R.
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Updated
Apr 9, 2023 - R
Calculating robust effect sizes using bootstrap (resampling) technique in R.
Performed a probabilistic analysis on sample GPA data using techniques such as Empirical distribution, Bootstrapping and Bayesian Analysis.
R programming and its application to data analysis and statistical methods
Review of bootstrap principles and coverage analysis of bootstrap confidence intervals for common estimators
EDOIF is a nonparametric framework based on estimation statistics principle. Its main purpose is to infer orders of empirical distributions from different categories base on a probability of finding a value in one distribution that greater than the expectation of another distribution.
Scripts developed for the Data Visualisation class
jeksterslabRboot is a collection of functions that I find useful in studying bootstrapping concepts and methods.
This R package provides scoring mechanisms for computational challenges and implements the bayesBootLadderBoot approach for avoiding test data leakage.
Master's thesis
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