Robust Analysis of Variance
碩士 === 國立中央大學 === 統計研究所 === 97 === Under the generalized multiple linear regression, Tsou(2009) proposed the robust likelihood method for normal working model. Even if the working model is wrong, it still provides correct inferences for the parameter of interest. We focus on applying the robust...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2009
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| Online Access: | http://ndltd.ncl.edu.tw/handle/64999971403528399063 |
| Summary: | 碩士 === 國立中央大學 === 統計研究所 === 97 === Under the generalized multiple linear regression, Tsou(2009) proposed the robust likelihood method for normal working model. Even if the working model is wrong, it still provides correct inferences for the parameter of interest.
We focus on applying the robust method to the analysis of variance, and further revising the F statistic and the likelihood ratio statistic. Using the robust F statistic can correctly infer the significance of regressors. The robust analysis of variance can still provide correct statistical analysis for a regression model, even if the normal assumption is improper. The efficacy of the proposed robust method is demonstrated via simulation studies and real data analyses.
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