A Simple Normal Approximation for Weibull Distribution with Application to Estimation of Upper Prediction Limit
Joint Authors
Source
Journal of Probability and Statistics
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-11-20
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
We propose a simple close-to-normal approximation to a Weibull random variable (r.v.) and consider the problem of estimation of upper prediction limit (UPL) that includes at least l out of m future observations from a Weibull distribution at each of r locations, based on the proposed approximation and the well-known Box-Cox normal approximation.
A comparative study based on Monte Carlo simulations revealed that the normal approximation-based UPLs for Weibull distribution outperform those based on the existing generalized variable (GV) approach.
The normal approximation-based UPLs have markedly larger coverage probabilities than GV approach, particularly for small unknown shape parameter where the distribution is highly skewed, and for small sample sizes which are commonly encountered in industrial applications.
Results are illustrated with a real dataset for practitioners.
American Psychological Association (APA)
Kulkarni, H. V.& Powar, S. K.. 2011. A Simple Normal Approximation for Weibull Distribution with Application to Estimation of Upper Prediction Limit. Journal of Probability and Statistics،Vol. 2011, no. 2011, pp.1-10.
https://search.emarefa.net/detail/BIM-504373
Modern Language Association (MLA)
Kulkarni, H. V.& Powar, S. K.. A Simple Normal Approximation for Weibull Distribution with Application to Estimation of Upper Prediction Limit. Journal of Probability and Statistics No. 2011 (2011), pp.1-10.
https://search.emarefa.net/detail/BIM-504373
American Medical Association (AMA)
Kulkarni, H. V.& Powar, S. K.. A Simple Normal Approximation for Weibull Distribution with Application to Estimation of Upper Prediction Limit. Journal of Probability and Statistics. 2011. Vol. 2011, no. 2011, pp.1-10.
https://search.emarefa.net/detail/BIM-504373
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-504373