Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0026-2714(99)00085-2
Title: Maximum likelihood predictive densities for the inverse Gaussian distribution with applications to reliability and lifetime predictions
Authors: Yang, Z. 
Issue Date: Sep-1999
Citation: Yang, Z. (1999-09). Maximum likelihood predictive densities for the inverse Gaussian distribution with applications to reliability and lifetime predictions. Microelectronics Reliability 39 (9) : 1413-1421. ScholarBank@NUS Repository. https://doi.org/10.1016/S0026-2714(99)00085-2
Abstract: Maximum likelihood predictive densities (MLPD) for the inverse Gaussian distribution are derived for the cases of one or both parameters unknown. They are then applied to obtain estimators of the reliability function and prediction or shortest prediction intervals for a future observation. Comparisons with the existing likelihood or frequentist methods show that the MLPD estimators of reliability gives smaller bias and smaller MSE for a wide range of population values, and that the MLPD prediction intervals are shorter while preserving the correct coverage probability. The shortest MLPD prediction intervals further sharpen the above equitailed MLPD intervals in terms of interval lengths.
Source Title: Microelectronics Reliability
URI: http://scholarbank.nus.edu.sg/handle/10635/105215
ISSN: 00262714
DOI: 10.1016/S0026-2714(99)00085-2
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

7
checked on Dec 11, 2018

WEB OF SCIENCETM
Citations

7
checked on Dec 11, 2018

Page view(s)

25
checked on Dec 7, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.