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...
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| Language: | en_US |
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Kansas State University
2013
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| Online Access: | http://hdl.handle.net/2097/16534 |
| Summary: | 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. |
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