Robust mixture linear EIV regression models by t-distribution

Date

2012-12-10

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

Citation