We have previously discussed the importance of estimating uncertainty in our measurements and incorporating it into data analysis 1. To know the extent to which we can generalize our observations, we ...

ABSTRACT: Many operations carried out by official statistical institutes use large-scale surveys obtained by stratified random sampling without replacement. Variables commonly examined in this type of ...

Studies on the iteration procedure in double bootstrap method have given a great impact on confidence interval performance. However, the procedure was claimed to be complicated and demand intensive ...

This project focuses on applying bootstrap sampling, a powerful resampling method, to improve the evaluation of machine learning models. The project uses the Scikit-learn Breast Cancer Diagnostics ...

The parametric bootstrap can be used for the efficient computation of Bayes posterior distributions. Importance sampling formulas take on an easy form relating to the deviance in exponential families, ...

Overview This GitHub repository contains code and analysis for a research project focused on analyzing fish length data using bootstrap methods. The project aims to estimate population parameters such ...