Parameter estimation for a finite mixture model in high dimensional applications

Author

Qinfang Xiang

Abstract

"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, page iii.

Advisor(s)

Gadbury, Gary L.

Committee Member(s)

Le, Vy Khoi
Frank, Ronald L.
Samaranayake, V. A.
Wen, Xuerong

Department(s)

Mathematics and Statistics

Degree Name

Ph. D. in Mathematics

Sponsor(s)

National Institutes of Health (U.S.)
National Science Foundation (U.S.)

Publisher

University of Missouri--Rolla

Publication Date

Fall 2006

Pagination

xi, 106 pages

Note about bibliography

Includes bibliographical references (pages 97-105).

Rights

© 2006 Qinfang Xiang, All rights reserved.

Document Type

Dissertation - Citation

File Type

text

Language

English

Subject Headings

AlgorithmsBootstrap (Statistics)Estimation theoryInterval analysis (Mathematics)Sampling (Statistics)

Thesis Number

T 9055

Print OCLC #

163215476

Recommended Citation

Xiang, Qinfang, "Parameter estimation for a finite mixture model in high dimensional applications" (2006). Doctoral Dissertations. 1699.
https://scholarsmine.mst.edu/doctoral_dissertations/1699