Title

Transformation Approaches for the Construction of Weibull Prediction Interval

Publication Type

Journal Article

Publication Date

2003

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.

Keywords

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

Discipline

Econometrics

Research Areas

Econometrics

Publication

Computational Statistics and Data Analysis

Volume

43

Issue

3

First Page

357

Last Page

368

ISSN

0167-9473

Identifier

10.1016/s0167-9473(02)00232-3

Publisher

Elsevier

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.1016/s0167-9473(02)00232-3

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