Robust weighted least squares estimation of regression parameter in the presence of outliers and heteroscedastic errors
In a linear regression model, the ordinary least squares (OLS) method is considered the best method to estimate the regression parameters if the assumptions are met. However, if the data does not satisfy the underlying assumptions, the results will be misleading. The violation for the assumption of...
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| 主要な著者: | , , , |
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| フォーマット: | 論文 |
| 出版事項: |
Penerbit UTM Press
2014
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| オンライン･アクセス: | http://eprints.utm.my/id/eprint/62501/ http://dx.doi.org/10.11113/jt.v71.3609 |
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