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Robust mixture regression model fitting by Laplace distribution

Master of Science / Department of Statistics / Weixing Song / A robust estimation procedure for mixture linear regression models is proposed in this
report by assuming the error terms follow a Laplace distribution. EM algorithm is imple-
mented to conduct the estimation procedure of missing information based on the fact that
the Laplace distribution is a scale mixture of normal and a latent distribution. Finite sample
performance of the proposed algorithm is evaluated by some extensive simulation studies,
together with the comparisons made with other existing procedures in this literature. A
sensitivity study is also conducted based on a real data example to illustrate the application of the proposed method.

Identiferoai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/16534
Date January 1900
CreatorsXing, Yanru
PublisherKansas State University
Source SetsK-State Research Exchange
Languageen_US
Detected LanguageEnglish
TypeReport

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