Parameter estimation for a finite mixture model in high dimensional applications
"Finite mixture models have found use in the analysis of high dimensional data such as result from microarray experiments. A common goal of a microarray experiment is to identify genes that express differentially between two types of tissues or between two experimental conditions. Some investigators found that the distribution of P-values from tests for differential genetic expression contains useful information regarding several quantities of interest. A uniform-beta mixture distribution (mix-o-matic) has been employed to model this distribution...This dissertation covers three topics: 1) the performance of interval estimates of model parameters using three computational methods including a comparison of the computational methods; 2: a relatively recent approach based on a number theoretic method for obtaining MLEs, its extensions and a comparison to Newton-type methods; 3) FDR estimation in the mix-o-matic and a comparison with eight other techniques for estimating FDR, all techniques making use of information in the distribution of P-values"--Abstract, leaf iii.
Gadbury, Gary L.
Le, Vy Khoi
Frank, Ronald L.
Samaranayake, V. A.
Mathematics and Statistics
Ph. D. in Mathematics
National Institute of Health (U.S.)
National Science Foundation (U.S.)
University of Missouri--Rolla
xi, 106 leaves
© 2006 Qinfang Xiang, All rights reserved.
Dissertation - Citation
Library of Congress Subject Headings
Interval analysis (Mathematics)
Print OCLC #
Link to Catalog Record
Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.http://laurel.lso.missouri.edu/record=b5927808~S5
Xiang, Qinfang, "Parameter estimation for a finite mixture model in high dimensional applications" (2006). Doctoral Dissertations. 1699.
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