Generalized co-sparse factor regression (GOFAR) is proposed, which utilizes the flexible vector generalized linear model framework and encodes the outcome ...

Oct 16, 2020 · Generalized co-sparse factor regression (GOFAR) is proposed, which utilizes the flexible vector generalized linear model framework and encodes the outcome ...

Multivariate regression techniques are commonly applied to explore the associations between large numbers of outcomes and predictors.

Sep 8, 2024 · Multivariate regression techniques are commonly applied to explore the associations between large numbers of outcomes and predictors.

Oct 21, 2020 · Multivariate regression techniques are commonly applied to explore the asso- ciations between large numbers of outcomes and predictors.

Mar 2, 2022 · Page 1. Package 'gofar'. October 13, 2022. Type Package. Title Generalized Co-Sparse Factor Regression. Version 0.1. Date 2022-02-26.

Multivariate regression techniques are commonly applied to explore the associations between large numbers of outcomes and predictors.

Oct 19, 2020 · Multivariate regression techniques are commonly applied to explore the asso- ciations between large numbers of outcomes and predictors.

Find and access allergic, infectious and immune-mediated disease data by searching across biomedical data repositories with the NIAID Data Discovery Portal.

Summary We develop a Bayesian methodology aimed at simultaneously estimating low-rank and row-sparse matrices in a high-dimensional multiple-response linear ...