Provide methods to perform customized inference at individual level by taking contextual covariates into account. Three main functions are provided in this package: (i) LASER(): it generates specially-designed artificial relevant samples for a given case; (ii) g2l.proc(): computes customized fdr(z|x); and (iii) rEB.proc(): performs empirical Bayes inference based on LASERs. The details can be found in Mukhopadhyay, S., and Wang, K (2021, <doi:10.48550/arXiv.2004.09588>).
Version: 3.3 Depends: R (≥ 4.0.3), stats, BayesGOF, MASS Imports: leaps, locfdr, Bolstad2, reshape2, ggplot2, polynom, glmnet, caret Published: 2022-05-18 DOI: 10.32614/CRAN.package.LPRelevance Author: Subhadeep Mukhopadhyay, Kaijun Wang Maintainer: Kaijun Wang <kaijunwang.19 at gmail.com> License: GPL-2 NeedsCompilation: no CRAN checks: LPRelevance results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=LPRelevance to link to this page.
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