Robust parameter-estimation using the bootstrap method for the 2-parameter Weibull distribution

Author

Seki, Tetsurou ; Yokoyama, Shin-ichiro

Author_Institution

Teiyo Univ. of Technol., Chiba, Japan

Volume

45

Issue

1

fYear

1996

fDate

3/1/1996 12:00:00 AM

Firstpage

34

Lastpage

41

Abstract

This paper proposes bootstrap robust estimation methods for the Weibull parameters; it applies bootstrap estimators of order statistics to the parametric estimation procedure. Estimates of the Weibull parameters are equivalent to the estimates using the extreme value distribution. Therefore, the bootstrap estimators of order statistics for the parameters of the extreme value distribution are examined. Accuracy and robustness for outliers are examined by Monte Carlo experiments which indicate adequate efficiency of the proposed reliability estimators for data with some outliers

Keywords

Monte Carlo methods; Weibull distribution; bootstrapping; estimation theory; parameter estimation; reliability theory; Monte Carlo experiments; accuracy; bootstrap method; efficiency; extreme value distribution; order statistics; reliability estimators; robust parameter estimation; two-parameter Weibull distribution; Life testing; Maximum likelihood estimation; Monte Carlo methods; Parameter estimation; Parametric statistics; Reliability theory; Robustness; Shape; Statistical distributions; Weibull distribution;

fLanguage

English

Journal_Title

Reliability, IEEE Transactions on

Publisher

ieee

ISSN

0018-9529

Type

jour

DOI

10.1109/24.488914

Filename

488914