Package: imv 0.3
Ben Domingue
imv: Model Comparison via the 'InterModel Vigorish' ('IMV')
Computes the 'InterModel Vigorish' ('IMV'), a metric for comparing the predictive accuracy of two models for binary outcomes. The 'IMV' is derived from the expected value of a bettor using one model's predicted probabilities against those of a competing model, and is estimated via k-fold cross-validation. Methods are provided for generalized linear models, mixed-effects models ('lme4'), and item response theory models ('mirt'). See <doi:10.1371/journal.pone.0316491>.
Authors:
imv_0.3.tar.gz
imv_0.3.tar.gz(r-4.7-any)imv_0.3.tar.gz(r-4.6-any)
imv_0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
imv/json (API)
NEWS
| # Install 'imv' in R: |
| install.packages('imv', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:0817dc6abb. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 123 | ||
| source / vignettes | OK | 184 | ||
| linux-release-x86_64 | OK | 128 | ||
| wasm-release | OK | 101 |
Exports:imvimv.binaryimv0glmimvglm.rmvar
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Cross-validated IMV for comparing two models | imv imv.default imv.glm |
| Compute IMV for binary outcomes | imv.binary |
| Cross-validated IMV for binomial mixed-effects models | imv.glmerMod |
| Cross-validated IMV for mirt IRT models | imv.SingleGroupClass |
| IMV for a GLM compared to a prevalence baseline | imv0glm |
| IMV for a GLM versus the same model with one variable removed | imvglm.rmvar |
