Bootstraps and imputes incomplete datasets. Then performs inference on estimates obtained from analysing the imputed datasets as proposed by von Hippel and Bartlett (2021) <doi:10.1214/20-STS793>.

Implementation of the bootkmeans algorithm, a bootstrap augmented k-means algorithm that returns probabilistic cluster assignments. From paper by Ghashti, J.S., Andrews, J.L. Thompson, J.R.J., Epp, J. and H.S. Kochar (2025), "A bootstrap augmented k-means algorithm for fuzzy partitions" (Submitted).

Computes appropriate confidence intervals for the likelihood ratio tests commonly used in medicine/epidemiology, using the method of Marill et al. (2015) <doi:10.1177/0962280215592907>.  It is particularly useful when the sensitivity or specificity in the sample is 100%.  Note that this does not perform the test on nested models--for that, see 'epicalc::lrtest'.

Implements three test procedures using bootstrap resampling techniques for assessing treatment effects in one-way ANOVA models with unequal variances (heteroscedasticity). It includes a parametric bootstrap likelihood ratio test (PB_LRT()), a pairwise parametric bootstrap mean test (PPBMT()), and a Rademacher wild pairwise non-parametric bootstrap test (RWPNPBT()). These methods provide robust alternatives to classical ANOVA and standard pairwise comparisons when the assumption of homogeneity of variances is violated.

Selection of informative features like genes, transcripts, RNA seq, etc. using Bootstrap Maximum Relevance and Minimum Redundancy technique from a given high dimensional genomic dataset. Informative gene selection involves identification of relevant genes and removal of redundant genes as much as possible from a large gene space. Main applications in high-dimensional expression data analysis (e.g. microarray data, NGS expression data and other genomics and proteomics applications).

Bootstrap methods to assess accuracy and stability of estimated network structures
              and centrality indices <doi:10.3758/s13428-017-0862-1>. Allows for flexible 
              specification of any undirected network estimation procedure in R, and offers 
              default sets for various estimation routines.