Generalized linear models with linear constraints for microbiome compositional data

DOI10.1111/biom.12956zbMath1436.62596arXiv1801.03238OpenAlexW2962797912WikidataQ90437425 ScholiaQ90437425MaRDI QIDQ5214468

Jiarui Lu, Pixu Shi, Hongzhe Li

Publication date: 7 February 2020

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1801.03238

zbMATH Keywords

high dimensional datametagenomicspenalized estimationaccelerated proximal gradientde-biased estimation

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items (8)

Sliced Inverse Regression in Metric Spaces ⋮ Compositional knockoff filter for high‐dimensional regression analysis of microbiome data ⋮ Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data ⋮ Three approaches to supervised learning for compositional data with pairwise logratios ⋮ Globally Adaptive Longitudinal Quantile Regression With High Dimensional Compositional Covariates ⋮ Robust Signal Recovery for High-Dimensional Linear Log-Contrast Models with Compositional Covariates ⋮ A review of compositional data analysis and recent advances ⋮ Robust logistic zero-sum regression for microbiome compositional data

This page was built for publication: Generalized linear models with linear constraints for microbiome compositional data