Transformation Approaches for the Construction of Weibull Prediction Interval

Transformation Approaches for the Construction of Weibull Prediction Interval

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 e...

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Bibliographic Details
Main Authors: YANG, Zhenlin, SEE, Stanley P., XIE, Min
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2003
Subjects:
Box-Cox transformation
Coverage probability
Kullback-Leibler information
Prediction interval
Weibull distribution
Econometrics
Online Access:https://ink.library.smu.edu.sg/soe_research/196
https://ink.library.smu.edu.sg/context/soe_research/article/1195/viewcontent/Transformation_Weibull_prediction_2003.pdf
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Institution: Singapore Management University
Language: English
Description
Summary: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.

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