Transformation approaches for the construction of Weibull prediction interval

Zhenlin Yang; Stanley P. See; M. Xie

doi:10.1016/S0167-9473(02)00232-3

Transformation approaches for the construction of Weibull prediction interval

Zhenlin Yang, Stanley P. See, M. Xie

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

6 Citations (Scopus)

Abstract

Two methods of transforming the Weibull data to near normality, namely the Box-Cox method and Kullback-Leibler (KL) information method, are discussed and contrasted. A simple prediction interval (PI) based on the better KL information method is proposed. The asymptotic property of this interval is established. Its small sample behavior is investigated using Monte Carlo simulation. Simulation results show that this simple interval is close to the existing complicated PI where the percentage points of the reference distribution have to be either simulated or approximated. The proposed interval can also be easily adjusted to have the correct asymptotic coverage. © 2002 Elsevier Science B.V. All rights reserved.

Original language	English
Pages (from-to)	357-368
Journal	Computational Statistics and Data Analysis
Volume	43
Issue number	3
DOIs	https://doi.org/10.1016/S0167-9473(02)00232-3
Publication status	Published - 28 Jul 2003
Externally published	Yes

Research Keywords

Box-Cox transformation
Coverage probability
Kullback-Leibler information
Prediction interval
Weibull distribution

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10.1016/S0167-9473(02)00232-3

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title = "Transformation approaches for the construction of Weibull prediction interval",

abstract = "Two methods of transforming the Weibull data to near normality, namely the Box-Cox method and Kullback-Leibler (KL) information method, are discussed and contrasted. A simple prediction interval (PI) based on the better KL information method is proposed. The asymptotic property of this interval is established. Its small sample behavior is investigated using Monte Carlo simulation. Simulation results show that this simple interval is close to the existing complicated PI where the percentage points of the reference distribution have to be either simulated or approximated. The proposed interval can also be easily adjusted to have the correct asymptotic coverage. {\textcopyright} 2002 Elsevier Science B.V. All rights reserved.",

keywords = "Box-Cox transformation, Coverage probability, Kullback-Leibler information, Prediction interval, Weibull distribution",

author = "Zhenlin Yang and See, {Stanley P.} and M. Xie",

year = "2003",

month = jul,

day = "28",

doi = "10.1016/S0167-9473(02)00232-3",

language = "English",

volume = "43",

pages = "357--368",

journal = "Computational Statistics and Data Analysis",

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TY - JOUR

T1 - Transformation approaches for the construction of Weibull prediction interval

AU - Yang, Zhenlin

AU - See, Stanley P.

AU - Xie, M.

PY - 2003/7/28

Y1 - 2003/7/28

N2 - Two methods of transforming the Weibull data to near normality, namely the Box-Cox method and Kullback-Leibler (KL) information method, are discussed and contrasted. A simple prediction interval (PI) based on the better KL information method is proposed. The asymptotic property of this interval is established. Its small sample behavior is investigated using Monte Carlo simulation. Simulation results show that this simple interval is close to the existing complicated PI where the percentage points of the reference distribution have to be either simulated or approximated. The proposed interval can also be easily adjusted to have the correct asymptotic coverage. © 2002 Elsevier Science B.V. All rights reserved.

AB - Two methods of transforming the Weibull data to near normality, namely the Box-Cox method and Kullback-Leibler (KL) information method, are discussed and contrasted. A simple prediction interval (PI) based on the better KL information method is proposed. The asymptotic property of this interval is established. Its small sample behavior is investigated using Monte Carlo simulation. Simulation results show that this simple interval is close to the existing complicated PI where the percentage points of the reference distribution have to be either simulated or approximated. The proposed interval can also be easily adjusted to have the correct asymptotic coverage. © 2002 Elsevier Science B.V. All rights reserved.

KW - Box-Cox transformation

KW - Coverage probability

KW - Kullback-Leibler information

KW - Prediction interval

KW - Weibull distribution

UR - http://www.scopus.com/inward/record.url?scp=0037593430&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0037593430&origin=recordpage

U2 - 10.1016/S0167-9473(02)00232-3

DO - 10.1016/S0167-9473(02)00232-3

M3 - RGC 21 - Publication in refereed journal

SN - 0167-9473

VL - 43

SP - 357

EP - 368

JO - Computational Statistics and Data Analysis

JF - Computational Statistics and Data Analysis

IS - 3

ER -

Transformation approaches for the construction of Weibull prediction interval

Abstract

Research Keywords

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