Combining isotonic regression and EM algorithm to predict genetic risk under monotonicity constraint

DOI10.1214/14-AOAS730zbMath1454.62380arXiv1407.8412WikidataQ34510437 ScholiaQ34510437MaRDI QIDQ400675

Ming-Xin Tang, Tanya P. Garcia, Yuanjia Wang, Karen Marder, Yanyuan Ma, Jing Qin

Publication date: 22 August 2014

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

Full work available at URL: https://arxiv.org/abs/1407.8412

zbMATH Keywords

Parkinson's diseasebinomial likelihoodpool adjacent violation algorithmself-consistency estimating equations

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (7)

Subgroup analysis with a nonparametric unimodal symmetric error distribution ⋮ Combining isotonic regression and EM algorithm to predict genetic risk under monotonicity constraint ⋮ A semiparametric isotonic regression model for skewed distributions with application to DNA–RNA–protein analysis ⋮ Maximum profile binomial likelihood estimation for the semiparametric Box-Cox power transformation model ⋮ Semiparametric mixture of regression models under unimodal error distribution ⋮ Maximum smoothed likelihood component density estimation in mixture models with known mixing proportions ⋮ Maximum multinomial likelihood estimation in compound mixture model with application to malaria study

Uses Software

• isotone

Cites Work

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• Maximum likelihood estimation of ordered multinomial parameters
• An Optimum Property of Regular Maximum Likelihood Estimation

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