Premium
Empirical likelihood‐based inference for genetic mixture models
Author(s) -
Huang ChiungYu,
Qin Jing,
Zou Fei
Publication year - 2007
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.5550350407
Subject(s) - empirical likelihood , inference , nonparametric statistics , statistics , confidence interval , statistic , likelihood ratio test , econometrics , genetic model , mathematics , computer science , biology , genetics , artificial intelligence , gene
The authors show how the genetic effect of a quantitative trait locus can be estimated by a nonparametric empirical likelihood method when the phenotype distributions are completely unspecified. They use an empirical likelihood ratio statistic for testing the genetic effect and obtaining confidence intervals. In addition to studying the asymptotic properties of these procedures, the authors present simulation results and illustrate their approach with a study on breast cancer resistance genes.