Packaged: 2019-09-05 21:00:30 UTC; AquinasUnit

Packaged: 2019-10-07 20:10:41 UTC; AquinasUnit

Package: LPRelevance
Type: Package
Title: Relevance-Integrated Statistical Inference Engine
Version: 3.0
Date: 2020-03-28
Author: Subhadeep Mukhopadhyay, Kaijun Wang
Maintainer: Kaijun Wang <kwang2@fredhutch.org>
Description: A framework of 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 (2020, Technical Report).
Imports: leaps,locfdr,Bolstad2,reshape2,ggplot2,polynom,glmnet,caret
Depends: R (>= 3.5.0), stats, BayesGOF, MASS
License: GPL-2
NeedsCompilation: no
Packaged: 2020-03-29 19:25:06 UTC; AquinasUnit
Repository: CRAN
Date/Publication: 2020-03-29 20:10:02 UTC

Package: LPRelevance
Type: Package
Title: Relevance-Integrated Statistical Inference Engine
Version: 3.1
Date: 2020-05-15
Author: Subhadeep Mukhopadhyay, Kaijun Wang
Maintainer: Kaijun Wang <kaijunwang.19@gmail.com>
Description: A framework of 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 (2020, Technical Report).
Imports: leaps,locfdr,Bolstad2,reshape2,ggplot2,polynom,glmnet,caret
Depends: R (>= 3.5.0), stats, BayesGOF, MASS
License: GPL-2
NeedsCompilation: no
Packaged: 2020-05-15 18:46:04 UTC; AquinasUnit
Repository: CRAN
Date/Publication: 2020-05-16 22:30:10 UTC

Description: Provide methods to perform customized inference at individual level by taking
contextual covariates into account. Three main functions are provided
found in Mukhopadhyay, S., and Wang, K (2021, <arXiv:2004.09588>).