This package is considered a duplicate. The official version of this package is found at:https://kaijunwang19.r-universe.dev/LPRelevance

Package: LPRelevance 3.3

Kaijun Wang

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>).

Authors:Subhadeep Mukhopadhyay, Kaijun Wang

LPRelevance_3.3.tar.gz
LPRelevance_3.3.zip(r-4.7)LPRelevance_3.3.zip(r-4.6)LPRelevance_3.3.zip(r-4.5)
LPRelevance_3.3.tgz(r-4.6-any)LPRelevance_3.3.tgz(r-4.5-any)
LPRelevance_3.3.tar.gz(r-4.7-any)LPRelevance_3.3.tar.gz(r-4.6-any)
LPRelevance_3.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
LPRelevance/json (API)

# Install 'LPRelevance' in R:

install.packages('LPRelevance', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

Datasets:

data.dti - DTI data.
funnel - A stylized simulated example.
kidney - Kidney data.

On CRAN:

archived packages r-universe

1.70 score 5 stars 168 downloads 20 exports 83 dependencies

Last updated from:456c7a65d3 (on package/LPRelevance). Checks:9 OK. Indexed: no.

Target	Result	Time
linux-devel-x86_64	OK	183
source / vignettes	OK	218
linux-release-x86_64	OK	173
macos-release-arm64	OK	92
macos-oldrel-arm64	OK	107
windows-devel	OK	170
windows-release	OK	159
windows-oldrel	OK	126
wasm-release	OK	110

Exports:eLP.poly eLP.poly.predict eLP.univar fdr.thresh g2l.infer g2l.infer.boot g2l.proc g2l.sampler get_bh_threshold getNullProb LASER LASER.rEB LP.post.conv LP.smooth LPcden LPregression Predict.LP.poly rEB.Finite.Bayes rEB.proc z.lp.center

Dependencies:BayesGOF Bolstad2 caret class cli clock codetools cpp11 data.table diagram digest dplyr e1071 farver foreach future future.apply generics ggplot2 glmnet globals glue gower gtable hardhat ipred isoband iterators KernSmooth labeling lattice lava leaps lifecycle listenv locfdr lubridate magrittr MASS Matrix ModelMetrics nleqslv nlme nnet numDeriv orthopolynom parallelly pillar pkgconfig plyr polynom pROC prodlim progressr proxy purrr R6 RColorBrewer Rcpp RcppEigen recipes reshape2 rlang rpart S7 scales shape sparsevctrs SQUAREM stringi stringr survival tibble tidyr tidyselect timechange timeDate tzdb utf8 vctrs VGAM viridisLite withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Relevance-Integrated Statistical Inference Engine	LPRelevance-package eLP.poly eLP.poly.predict eLP.univar LP.smooth LPcden LPregression LPRelevance Predict.LP.poly
DTI data.	data.dti
A stylized simulated example.	funnel
Procedures for global and local inference.	fdr.thresh g2l.infer g2l.infer.boot g2l.proc getNullProb get_bh_threshold
Kidney data.	kidney
Generates Artificial RELevance Samples.	g2l.sampler LASER z.lp.center
Relevance-Integrated Finite Bayes.	rEB.Finite.Bayes
Relevance-Integrated Empirical Bayes Inference	LASER.rEB LP.post.conv rEB.proc