A likelihood-based approach for multivariate categorical response regression in high dimensions

We propose a penalized likelihood method to fit the bivariate categorical response regression model. Our method allows practitioners to estimate which predictors are irrelevant, which predictors only affect the marginal distributions of the bivariate response, and which predictors affect both the ma...

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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Molstad, Aaron J, Rothman, Adam J
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 23.01.2022
Subjects:	Asymptotic methods Bivariate analysis Computer simulation First order algorithms Multivariate analysis Regression models
ISSN:	2331-8422
Online Access:	Get full text
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