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.
Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/16534 |
Date | January 1900 |
Creators | Xing, Yanru |
Publisher | Kansas State University |
Source Sets | K-State Research Exchange |
Language | en_US |
Detected Language | English |
Type | Report |
Page generated in 0.0031 seconds