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Provides methods for quantifying the information gain contributed by individual modalities in multimodal regression models. Information gain is measured using Expected Relative Entropy (ERE) or pseudo-R² metrics, with corresponding p-values and confidence intervals. Currently supports linear and logistic regression models with plans for extension to additional Generalized Linear Models and Cox proportional hazard model.
| Version: | 1.0 |
| Depends: | R (≥ 3.6.0) |
| Imports: | tidyverse, MASS, SIS, glmnet, ncvreg, MBESS, survival, dplyr |
| Published: | 2025-09-03 |
| DOI: | 10.32614/CRAN.package.multiModTest |
| Author: | Wanting Jin [aut, cre], Quefeng Li [aut] |
| Maintainer: | Wanting Jin <jinwanting5 at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | multiModTest results |
| Reference manual: | multiModTest.html , multiModTest.pdf |
| Package source: | multiModTest_1.0.tar.gz |
| Windows binaries: | r-devel: multiModTest_1.0.zip, r-release: multiModTest_1.0.zip, r-oldrel: multiModTest_1.0.zip |
| macOS binaries: | r-release (arm64): multiModTest_1.0.tgz, r-oldrel (arm64): multiModTest_1.0.tgz, r-release (x86_64): multiModTest_1.0.tgz, r-oldrel (x86_64): multiModTest_1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.