mvrsquared: Compute the Coefficient of Determination for Vector or Matrix Outcomes

Compute the coefficient of determination for outcomes in n-dimensions. May be useful for multidimensional predictions (such as a multinomial model) or calculating goodness of fit from latent variable models such as probabilistic topic models like latent Dirichlet allocation or deterministic topic models like latent semantic analysis. Based on Jones (2019) <arXiv:1911.11061>.

Version: 0.0.3
Imports: Matrix, methods, Rcpp (≥ 1.0.2)
LinkingTo: Rcpp, RcppArmadillo
Suggests: dplyr, furrr, knitr, MASS, nnet, parallel, rmarkdown, stats, stringr, testthat, textmineR, tidytext
Published: 2020-02-20
Author: Tommy Jones [aut, cre]
Maintainer: Tommy Jones <jones.thos.w at gmail.com>
BugReports: https://github.com/TommyJones/mvrsquared/issues
License: MIT + file LICENSE
URL: https://github.com/TommyJones/mvrsquared
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: mvrsquared results

Downloads:

Reference manual: mvrsquared.pdf
Vignettes: Getting Started With mvrsquared
Package source: mvrsquared_0.0.3.tar.gz
Windows binaries: r-devel: mvrsquared_0.0.3.zip, r-release: mvrsquared_0.0.3.zip, r-oldrel: mvrsquared_0.0.3.zip
macOS binaries: r-release: mvrsquared_0.0.3.tgz, r-oldrel: mvrsquared_0.0.3.tgz

Linking:

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