Robust mixture linear EIV regression models by t-distribution
Date
2012-12-10
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Kansas State University
Abstract
A robust estimation procedure for mixture errors-in-variables linear regression models is proposed in the report by assuming the error terms follow a t-distribution. The estimation procedure is implemented by an EM algorithm based on the fact that the t-distribution is a scale mixture of normal distribution and a Gamma distribution. Finite sample performance of the proposed algorithm is evaluated by some extensive simulation studies. Comparison is also made with the MLE procedure under normality assumption.
Description
Keywords
Robust estimation, Linear errors-in-variables model, EM algorithm, Mixture, T-distribution
Graduation Month
December
Degree
Master of Science
Department
Department of Statistics
Major Professor
Weixing Song
Date
2013
Type
Report