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: 0.1.5
Depends: R (≥ 3.0.2)
Imports: Matrix, methods, Rcpp (≥ 1.0.2)
LinkingTo: Rcpp, RcppArmadillo, RcppThread (≥ 2.1.3)
Suggests: dplyr, furrr, knitr, MASS, nnet, parallel, rmarkdown, stats, stringr, testthat, textmineR, tidytext, spelling
Published: 2023-07-15
Author: Tommy Jones ORCID iD [aut, cre], Thomas Nagler ORCID iD [ctb]
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
Language: en-US
Materials: README NEWS
CRAN checks: mvrsquared results

Documentation:

Reference manual: mvrsquared.pdf
Vignettes: Getting Started With mvrsquared

Downloads:

Package source: mvrsquared_0.1.5.tar.gz
Windows binaries: r-devel: mvrsquared_0.1.5.zip, r-release: mvrsquared_0.1.5.zip, r-oldrel: mvrsquared_0.1.5.zip
macOS binaries: r-release (arm64): mvrsquared_0.1.5.tgz, r-oldrel (arm64): mvrsquared_0.1.5.tgz, r-release (x86_64): mvrsquared_0.1.5.tgz
Old sources: mvrsquared archive

Reverse dependencies:

Reverse imports: tidylda

Linking:

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