Bootstrap Methods in a Class of Non-Linear Regression Models

Midi, Habshah (2000) Bootstrap Methods in a Class of Non-Linear Regression Models. Pertanika Journal of Science & Technology, 8 (2). pp. 175-189. ISSN 0128-7680

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Abstract

In this paper, the performances of the bootstrap standard errors (BSE) of the Weighted MM (WMM) estimates were compared with the Monte Carlo (MCSE) and Asymptotic (ASE) standard errors. The properties of the Percentile (PB), Bias-Corrected Persentile (BCP), Bias and Accelerated (BC), Studentized Percentile (SPB) and the Symmetric (SB) bootstrap confidenceaintervals of the WMM estimates were examined and compared. The results of the study indicate that the BSE is reasonably close to the ASE and MCSE for up to 20% outliers. The BCa has attractive properties in terms of better coverage probability, equitailness and average interval length compared to the other methods.

Item Type:Article
Keyword:Outlier, weighted MM, bootstrap sampling
Faculty or Institute:Faculty of Environmental Studies
Publisher:Universiti Putra Malaysia Press
ID Code:3511
Deposited By: Nur Izzati Mohd Zaki
Deposited On:30 Nov 2009 00:56
Last Modified:27 May 2013 07:09

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