Sparse probit linear mixed model

DOI10.1007/s10994-017-5652-6zbMath1460.62111arXiv1507.04777OpenAlexW2734755574MaRDI QIDQ1698863

Marius Kloft, Florian Wenzel, Stephan Mandt, Christoph Lippert, Shinichi Nakajima, John P. Cunningham

Publication date: 16 February 2018

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1507.04777

zbMATH Keywords

statistical geneticscausalityfeature selectionapproximate Bayesian inference

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Generalized linear models (logistic models) (62J12) Statistical aspects of big data and data science (62R07)

Related Items (1)

Computational causal discovery: Advantages and assumptions

Uses Software

• DREBIN
• Eigenstrat
• ccSVM

Cites Work

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