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iprior: Regression Modelling using I-Priors

Provides methods to perform and analyse I-prior regression models. Estimation is done either via direct optimisation of the log-likelihood or an EM algorithm.

Version: 0.7.4
Depends: R (≥ 3.2.5)
Imports: doSNOW, foreach, ggplot2, mvtnorm, Rcpp (≥ 0.12.5), reshape2, scales
LinkingTo: Rcpp, RcppEigen
Suggests: caret, knitr, MASS, R.rsp, rmarkdown, testthat
Published: 2024-04-01
DOI: 10.32614/CRAN.package.iprior
Author: Haziq Jamil [aut, cre]
Maintainer: Haziq Jamil <haziq.jamil at gmail.com>
BugReports: https://github.com/haziqj/iprior/issues
License: GPL (≥ 3.0)
URL: https://github.com/haziqj/iprior
NeedsCompilation: yes
Language: en-GB
Materials: README NEWS
CRAN checks: iprior results

Documentation:

Reference manual: iprior.pdf
Vignettes: Closed-form EM algorithm matrix manipulations
Regression with a functional covariate: Cross-validation analysis of the Tecator data set
An R Package for Regression Modelling Using I-priors

Downloads:

Package source: iprior_0.7.4.tar.gz
Windows binaries: r-devel: iprior_0.7.4.zip, r-release: iprior_0.7.4.zip, r-oldrel: iprior_0.7.4.zip
macOS binaries: r-release (arm64): iprior_0.7.4.tgz, r-oldrel (arm64): iprior_0.7.4.tgz, r-release (x86_64): iprior_0.7.4.tgz, r-oldrel (x86_64): iprior_0.7.4.tgz
Old sources: iprior archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=iprior to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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