Article

A Ranked Sparsity Extension to the Bayesian Information Criterion: A Tool for Selecting Variables from Multiple Data Modalities

2026-07-03

Abstract excerpt

The concept of ranked sparsity, originally introduced in the context of penalized regression, arises in modeling applications when an expected disparity exists in the quality of information between different feature sets. Its presence can cause traditional and modern model selection methods to fail because such procedures commonly presume “covariate equipoise” — that each potential parameter is equally worthy of e...

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Literature Corpus work: 8783a1a5-df60-5869-835c-f0cb161e002a
DOI: 10.20944/preprints202607.0193.v1

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