Package: HDBRR 1.1.4

HDBRR: High Dimensional Bayesian Ridge Regression without MCMC

Ridge regression provide biased estimators of the regression parameters with lower variance. The HDBRR ("High Dimensional Bayesian Ridge Regression") function fits Bayesian Ridge regression without MCMC, this one uses the SVD or QR decomposition for the posterior computation.

Authors:Sergio Perez-Elizalde Developer [aut], Blanca Monroy-Castillo Developer [aut, cre], Paulino Perez-Rodriguez User [ctb], Jose Crossa User [ctb]

HDBRR_1.1.4.tar.gz
HDBRR_1.1.4.zip(r-4.7)HDBRR_1.1.4.zip(r-4.6)HDBRR_1.1.4.zip(r-4.5)
HDBRR_1.1.4.tgz(r-4.6-any)HDBRR_1.1.4.tgz(r-4.5-any)
HDBRR_1.1.4.tar.gz(r-4.7-any)HDBRR_1.1.4.tar.gz(r-4.6-any)
HDBRR_1.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
HDBRR/json (API)

# Install 'HDBRR' in R:

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

Datasets:

pheno - Durum Wheat
X - Durum Wheat X

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 2 scripts 297 downloads 8 exports 45 dependencies

Last updated from:b672266198. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	143
source / vignettes	OK	236
linux-release-x86_64	NOTE	143
macos-release-arm64	NOTE	87
macos-oldrel-arm64	NOTE	80
windows-devel	NOTE	89
windows-release	NOTE	83
windows-oldrel	NOTE	124
wasm-release	OK	131

Exports:coef.HDBRR HDBRR matop plot.HDBRR predict.HDBRR print.HDBRR print.summary.HDBRR summary.HDBRR

Dependencies:bigassertr bigparallelr bigstatsr bit cli codetools cowplot cpp11 doParallel farver ff flock foreach ggplot2 glue gtable isoband iterators labeling lattice lifecycle magrittr MASS Matrix numDeriv parallelly pillar pkgconfig ps R6 RColorBrewer Rcpp RcppArmadillo RcppEigen RhpcBLASctl rlang rmio RSpectra S7 scales tibble utf8 vctrs viridisLite withr

HDBRR-extdoc

Introduction | Method and Materials | Results | Conclusions

Rendered fromHDBRR.Rnwusingutils::Sweave

Last update: 2022-10-05
Started: 2021-08-13

Help page	Topics
High Dimensional Bayesian Ridge Regression without MCMC.	coef.HDBRR HDBRR plot.HDBRR predict.HDBRR print.HDBRR print.summary.HDBRR summary.HDBRR
matop	matop
Durum Wheat	pheno
Durum wheat dataset	phenowheat
Durum Wheat X	X

Package: HDBRR 1.1.4

HDBRR: High Dimensional Bayesian Ridge Regression without MCMC

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)