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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Muda, N. |
| Copyright Year | 2009 |
| Description | Author affiliation: School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600Bangi Selangor, Malaysia (Muda, N.) |
| Abstract | In designed experiments, we often encountered nonnormal response variables. The data transformations (Transf) approached are frequently employed to deal with these problems. One has to realize that analyzing such data based on transformations posed many drawbacks. A better approach in dealing with these problems is by using the Generalized Linear Model (GLM). The problem becomes more complicated when there existed outlier in the data set. As an alternative, we may turn to robust (M- based) Generalized Linear Model (GLM) technique, which is less affected by outlier. In this paper we investigate the performance of the M-based GLM by doing the Monte Carlo simulation and its performance is compared to the Transf. and the GLM techniques. The empirical evidence shows that the M-based GLM is slightly better than the GLM and the Transf. approach in a well-behaved data. However, when contamination occurs in the data, its performance is remarkably robust with respect to outlier and non-normal responses. |
| Starting Page | 596 |
| Ending Page | 599 |
| File Size | 190719 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424450534 |
| DOI | 10.1109/NABIC.2009.5393419 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-12-09 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Maximum likelihood estimation Data analysis Generalized linear model Quasi-likelihood estimator Least squares approximation Least squares methods Contamination Design engineering Mestimator Robustness Transformations Random variables Mathematical model Analysis of variance |
| Content Type | Text |
| Resource Type | Article |
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