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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Main Authors: Adnan, Robiah, Saffari, Seyed Ehsan, Pati, Kafi Dano, Rasheed, Abdulkadir Bello
格式: Article
出版: Penerbit UTM Press 2014
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在線閱讀:http://eprints.utm.my/id/eprint/62501/
http://dx.doi.org/10.11113/jt.v71.3609
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