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 |
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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 [aut, cre], Thomas Nagler [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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