Bootstrap Methods in a Class of Non-Linear Regression Models

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 Pe...

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Main Author: Midi, Habshah
Format: Article
Language:English
English
Published: Universiti Putra Malaysia Press 2000
Online Access:http://psasir.upm.edu.my/id/eprint/3511/
http://psasir.upm.edu.my/id/eprint/3511/1/Bootstrap_Methods_in_a_Class_of_Non-Linear.pdf
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author Midi, Habshah
author_facet Midi, Habshah
author_sort Midi, Habshah
building UPM Institutional Repository
collection Online Access
description 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.
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spelling upm-35112013-05-27T07:09:05Z http://psasir.upm.edu.my/id/eprint/3511/ Bootstrap Methods in a Class of Non-Linear Regression Models Midi, Habshah 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. Universiti Putra Malaysia Press 2000 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/3511/1/Bootstrap_Methods_in_a_Class_of_Non-Linear.pdf 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 English
spellingShingle Midi, Habshah
Bootstrap Methods in a Class of Non-Linear Regression Models
title Bootstrap Methods in a Class of Non-Linear Regression Models
title_full Bootstrap Methods in a Class of Non-Linear Regression Models
title_fullStr Bootstrap Methods in a Class of Non-Linear Regression Models
title_full_unstemmed Bootstrap Methods in a Class of Non-Linear Regression Models
title_short Bootstrap Methods in a Class of Non-Linear Regression Models
title_sort bootstrap methods in a class of non-linear regression models
url http://psasir.upm.edu.my/id/eprint/3511/
http://psasir.upm.edu.my/id/eprint/3511/1/Bootstrap_Methods_in_a_Class_of_Non-Linear.pdf