doi:10.48550/arXiv.1911.11061>.">

mvrsquared: Compute the Coefficient of Determination for Vector or Matrix Outcomes (original) (raw)

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) <doi:10.48550/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
DOI: 10.32614/CRAN.package.mvrsquared
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
URL: https://github.com/TommyJones/mvrsquared
NeedsCompilation: yes
Language: en-US
Materials: README NEWS
CRAN checks: mvrsquared results

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