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, <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 |
| Author: |
Subhadeep Mukhopadhyay, Kaijun Wang |
| Maintainer: |
Kaijun Wang <kaijunwang.19 at gmail.com> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| CRAN checks: |
LPRelevance results |
Documentation:
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