Prediction of tumour pathological subtype from genomic profile using sparse logistic regression with random effects

DOI10.1080/02664763.2020.1738358OpenAlexW3012296382MaRDI QIDQ5861537

Özlem Kaymaz, Khaled Alqahtani, Henry M. Wood, Arief Gusnanto

Publication date: 1 March 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://eprints.whiterose.ac.uk/158919/1/subtype-HL5.pdf

zbMATH Keywords

logistic regressionsparse solutiontumourhierarchical likelihoodlung cancerpathological subtype

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• plsgenomics

Cites Work

• Least angle regression. (With discussion)
• Coordinate descent algorithms for lasso penalized regression
• A new sparse variable selection via random-effect model
• Regularization and Variable Selection Via the Elastic Net
• Generalized Linear Models with Random Effects
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Lasso Regression: Estimation and Shrinkage via the Limit of Gibbs Sampling
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