LPRelevance: Relevance-Integrated Statistical Inference Engine
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 formhttps://CRAN.R-project.org/package=LPRelevanceto link to this page.