Model selection and sensitivity analysis for sequence pattern models
Statistics Theory
2008-12-18 v1 Methodology
Statistics Theory
Abstract
In this article we propose a maximal a posteriori (MAP) criterion for model selection in the motif discovery problem and investigate conditions under which the MAP asymptotically gives a correct prediction of model size. We also investigate robustness of the MAP to prior specification and provide guidelines for choosing prior hyper-parameters for motif models based on sensitivity considerations.
Keywords
Cite
@article{arxiv.0805.2523,
title = {Model selection and sensitivity analysis for sequence pattern models},
author = {Mayetri Gupta},
journal= {arXiv preprint arXiv:0805.2523},
year = {2008}
}
Comments
Published in at http://dx.doi.org/10.1214/193940307000000301 the IMS Collections (http://www.imstat.org/publications/imscollections.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)