DSLRIG: Leveraging predictor structure in logistic regression

DOI10.1080/03610918.2019.1586927zbMath1497.62016OpenAlexW2926618019MaRDI QIDQ5082634

R. Ayesha Ali, E. James Squires, Flavio Schenkel, Gerarda A. Darlington, Matthew Stephenson

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2019.1586927

zbMATH Keywords

logistic regressionhigh-dimensional datavariable selectionundirected graphsSNP data

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Generalized linear models (logistic models) (62J12) Probabilistic graphical models (62H22)

Related Items

Multiclass sparse discriminant analysis incorporating graphical structure among predictors

Uses Software

• Matlab
• R
• mvtnorm
• huge

Cites Work

• Computation of multivariate normal and \(t\) probabilities
• High-dimensional graphs and variable selection with the Lasso
• Doubly sparse regression incorporating graphical structure among predictors