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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.5 |
rolling linux/jammy R-4.5 | mvrsquared_0.1.5.tar.gz |
218.7 KiB |
0.1.5 |
rolling linux/noble R-4.5 | mvrsquared_0.1.5.tar.gz |
221.2 KiB |
0.1.5 |
rolling source/ R- | mvrsquared_0.1.5.tar.gz |
122.2 KiB |
0.1.5 |
latest linux/jammy R-4.5 | mvrsquared_0.1.5.tar.gz |
218.7 KiB |
0.1.5 |
latest linux/noble R-4.5 | mvrsquared_0.1.5.tar.gz |
221.2 KiB |
0.1.5 |
latest source/ R- | mvrsquared_0.1.5.tar.gz |
122.2 KiB |
0.1.5 |
2026-04-26 source/ R- | mvrsquared_0.1.5.tar.gz |
122.2 KiB |
0.1.5 |
2026-04-23 source/ R- | mvrsquared_0.1.5.tar.gz |
122.2 KiB |
0.1.5 |
2026-04-09 windows/windows R-4.5 | mvrsquared_0.1.5.zip |
628.8 KiB |
0.1.5 |
2025-04-20 source/ R- | mvrsquared_0.1.5.tar.gz |
122.2 KiB |