Please use this identifier to cite or link to this item:
|Title:||Predicting a Future Lifetime through Box-Cox Transformation|
|Source:||Yang, Z. (1999). Predicting a Future Lifetime through Box-Cox Transformation. Lifetime Data Analysis 5 (3) : 265-279. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1009676116509|
|Abstract:||In predicting a future lifetime based on a sample of past lifetimes, the Box-Cox transformation method provides a simple and unified procedure that is shown in this article to meet or often outperform the corresponding frequentist solution in terms of coverage probability and average length of prediction intervals. Kullback-Leibler information and second-order asymptotic expansion are used to justify the Box-Cox procedure. Extensive Monte Carlo simulations are also performed to evaluate the small sample behavior of the procedure. Certain popular lifetime distributions, such as Weibull, inverse Gaussian and Birnbaum-Saunders are served as illustrative examples. One important advantage of the Box-Cox procedure lies in its easy extension to linear model predictions where the exact frequentist solutions are often not available.|
|Source Title:||Lifetime Data Analysis|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Feb 28, 2018
WEB OF SCIENCETM
checked on Feb 21, 2018
checked on Feb 27, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.