Journal article
A Bayesian nonparametric method for model evaluation: application to genetic studies
Abstract
Statistical models applied to genetic studies commonly assume linear relationships (between disease and risk factors) and simple distributional forms (by relying on asymptotic methods) for inference. However, when the sample size is small, inference using traditional asymptotic models can be problematic. Moreover, the gene-disease relationship is not always linear. In this article, we present a new nonparametric Bayesian method for model …
Authors
Shahbaba B; Gentles AJ; Beyene J; Plevritis SK; Greenwood CMT
Journal
Journal of Nonparametric Statistics, Vol. 21, No. 3, pp. 379–396
Publisher
Taylor & Francis
Publication Date
April 2009
DOI
10.1080/10485250802613558
ISSN
1048-5252