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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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書誌詳細
主要な著者:	Adnan, Robiah, Saffari, Seyed Ehsan, Pati, Kafi Dano, Rasheed, Abdulkadir Bello
フォーマット:	論文
出版事項:	Penerbit UTM Press 2014
主題:	Q Science
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
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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