Robust Regression with Continuous and Categorical Variables Having Heteroscedastic Non-Normal Errors

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Robust Regression with Continuous and Categorical Variables Having Heteroscedastic Non-Normal Errors

The performance of the classical Ordinary Least Squares (OLS) method can be very poor when the data set for which one often makes a normal assumption, has a heavy- tailed distribution which may arise as a result of outliers. The problem is further complicated when the variances of the error terms a...

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Bibliographic Details
Main Author:	Majeed Al-Talib, Bashar Abdul Aziz
Format:	Thesis
Language:	English English
Published:	2006
Subjects:	Regression analysis Heteroscedasticity Analysis of variance
Online Access:	http://psasir.upm.edu.my/id/eprint/546/ http://psasir.upm.edu.my/id/eprint/546/1/600391_fs_2006_52_abstrak_je__dh_pdf_.pdf

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