Outlier Detections and Robust Estimation Methods for Nonlinear Regression Model Having Autocorrelated and Heteroscedastic Errors

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Outlier Detections and Robust Estimation Methods for Nonlinear Regression Model Having Autocorrelated and Heteroscedastic Errors

The ordinary Nonlinear Least Squares (NLLS) and the Maximum Likelihood Estimator (MLE) techniques are often used to estimate the parameters of nonlinear models. Unfortunately, many researchers are not aware of the consequences of using such estimators when outliers are present in the data. The prob...

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Bibliographic Details
Main Author:	Riazoshams, Hossein
Format:	Thesis
Language:	English English
Published:	2010
Subjects:	Outliers (Statistics) Regression analysis - Mathematical models. Autocorrelation (Statistics)
Online Access:	http://psasir.upm.edu.my/id/eprint/19681/ http://psasir.upm.edu.my/id/eprint/19681/1/IPM_2010_13.pdf

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