Introduction | Method and Materials | Results | Conclusions
Package: HDBRR 1.1.5
HDBRR: High Dimensional Bayesian Ridge Regression without MCMC
Implements Bayesian ridge regression for high-dimensional data without using Markov chain Monte Carlo (MCMC). Posterior computations are performed using singular value decomposition (SVD) or QR decomposition. The package also provides variable selection and prediction methods.
Authors:
HDBRR_1.1.5.tar.gz
HDBRR_1.1.5.zip(r-4.7-any)HDBRR_1.1.5.zip(r-4.6-any)HDBRR_1.1.5.zip(r-4.5-any)
HDBRR_1.1.5.tgz(r-4.6-any)HDBRR_1.1.5.tgz(r-4.5-any)
HDBRR_1.1.5.tar.gz(r-4.7-any)HDBRR_1.1.5.tar.gz(r-4.6-any)
HDBRR_1.1.5.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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:5f45f8a865. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 168 | ||
| source / vignettes | OK | 326 | ||
| linux-release | OK | 134 | ||
| macos-release | OK | 144 | ||
| macos-oldrel | OK | 102 | ||
| windows-devel | OK | 65 | ||
| windows-release | OK | 78 | ||
| windows-oldrel | OK | 79 | ||
| wasm-release | OK | 102 |
Dependencies:bigassertrbigparallelrbigstatsrbitclicodetoolscowplotcpp11doParallelfarverffflockforeachggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMatrixnumDerivparallellypillarpkgconfigpsR6RColorBrewerRcppRcppArmadilloRcppEigenRhpcBLASctlrlangrmioRSpectraS7scalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Extract coefficients from an HDBRR model | coef.HDBRR |
| High Dimensional Bayesian Ridge Regression without MCMC. | HDBRR |
| matop | matop |
| Durum Wheat | pheno |
| Durum wheat dataset | phenowheat |
| Plot an HDBRR model | plot.HDBRR |
| Predict from an HDBRR model | predict.HDBRR |
| Print an HDBRR model | print.HDBRR print.summary.HDBRR |
| Summarize an HDBRR model | summary.HDBRR |
| Durum Wheat X | X |