Robust statistics is an extension of classical parametric statistics, which provides a safeguard against gross errors in experiments. Effectively, robustness properties of Uhlig's Q-estimators are examined and compared with that. of Rocke's Ai-estimators. In particular, the finite-sample implosion and explosion breakdown points are inves-tigated and introduced into constructing robust designs for the one-way random effects model. Optimal robust designs based on Uhlig's Q-estimation are similar to the ones based on Rocke's M-estimation. Ultimately. robust estimation procedures would provide steady and reliable estimates of model parameters in case of the occurrence of outliers.
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/1945 |
| Date | 04 December 2009 |
| Creators | Yang, Xiaolong |
| Contributors | Zhou, Julie |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
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