multiModTest: Information Assessment for Individual Modalities in Multimodal
Regression Models
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 confidence
intervals. Currently supports linear regression, logistic regression, and the Cox proportional
hazards model. A robust Median-of-Means based estimator is also provided
for heavy-tailed responses under the Gaussian and Negative-Binomial families, with basic
bootstrap confidence intervals.
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