Master of Science / Department of Statistics / Weixin Yao / In this report, we investigate a robust estimation of the number of components in the
mixture of regression models using trimmed information criterion. Compared to the traditional information criterion, the trimmed criterion is robust and not sensitive to outliers. The superiority of the trimmed methods in comparison with the traditional information
criterion methods is illustrated through a simulation study. A real data application is also
used to illustrate the effectiveness of the trimmed model selection methods.
| Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/17856 |
| Date | January 1900 |
| Creators | Meng, Li |
| Publisher | Kansas State University |
| Source Sets | K-State Research Exchange |
| Language | en_US |
| Detected Language | English |
| Type | Report |
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