Package: mvrsquared 0.1.5

Tommy Jones

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>.

Authors:Tommy Jones [aut, cre], Thomas Nagler [ctb]

mvrsquared_0.1.5.tar.gz
mvrsquared_0.1.5.tar.gz(r-4.5-noble)mvrsquared_0.1.5.tar.gz(r-4.4-noble)
mvrsquared_0.1.5.tgz(r-4.4-emscripten)mvrsquared_0.1.5.tgz(r-4.3-emscripten)
mvrsquared.pdf |mvrsquared.html✨
mvrsquared/json (API)
NEWS

# Install 'mvrsquared' in R:
install.packages('mvrsquared', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tommyjones/mvrsquared/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

3.26 score 1 packages 12 scripts 247 downloads 1 exports 5 dependencies

Last updated 1 years agofrom:5bf2ca9a64. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 25 2024
R-4.5-linux-x86_64OKOct 25 2024

Exports:calc_rsquared

Dependencies:latticeMatrixRcppRcppArmadilloRcppThread

Getting Started With mvrsquared

Tommy Jones

Rendered fromgetting_started_with_mvrsquared.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2020-06-25
Started: 2020-02-20