Seaman, John Weldon, 1956-Miyamoto, Kazutoshi.Baylor University. Dept. of Statistical Sciences.2008-10-142008-10-142008-082008-10-14http://hdl.handle.net/2104/5233Includes bibliographical references (p.84-86)The change-point (CP) problem, wherein parameters of a model change abruptly at an unknown covariate value, is common in many fields, such as process control, epidemiology, and ecology. CP problems using two-segment regression models, such as those based on generalized linear models, are very flexible and widely used. For two-segment Poisson and logistic regression models, misclassification in the response is well known to cause attenuation of key parameters and other difficulties. How misclassification effects estimation of a CP in such models has not been studied. In this research, we consider the effect of misclassification on CP problems in Poisson and logistic regression. We focus on maximum likelihood and Bayesian methods.xi, 86 p. : ill.538676 bytes154640 bytesapplication/pdfapplication/pdfen-USBaylor University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact librarywebmaster@baylor.edu for inquiries about permission.Change-point problems.Regression analysis.Linear models (Statistics).Bayesian statistical decision theory.Mathematical statistics.ThesisBaylor University access only