Title

Interval Estimation in a Finite Mixture Model: Modeling P-values in Multiple Testing Applications

Abstract

The performance of interval estimates in a uniform-beta mixture model is evaluated using three computational strategies. Such a model has found use when modeling a distribution of P-values from multiple testing applications. The number of P-values and the closeness of a parameter to the boundary of its space both play a role in the precision of parameter estimates as does the “nearness” of the beta-distribution component to the uniform distribution. Three computational strategies are compared for computing interval estimates with each one having advantages and disadvantages for cases considered here.

Department(s)

Mathematics and Statistics

Keywords and Phrases

Hessian; MCMC; Microarray; interval estimation

Library of Congress Subject Headings

Bootstrap (Statistics)
Gene expression

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2006 Elsevier, All rights reserved.

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