Maximum Likelihood Predictive Densities for the Inverse Gaussian Distribution with Application to Reliability and Lifetime Predictions
Publication Type
Journal Article
Publication Date
1999
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.
Discipline
Econometrics
Research Areas
Econometrics
Publication
Microelectronics Reliability
Volume
39
Issue
9
First Page
1413
Last Page
1421
ISSN
0026-2714
Identifier
10.1016/s0026-2714(99)00085-2
Citation
YANG, Zhenlin.
Maximum Likelihood Predictive Densities for the Inverse Gaussian Distribution with Application to Reliability and Lifetime Predictions. (1999). Microelectronics Reliability. 39, (9), 1413-1421.
Available at: https://ink.library.smu.edu.sg/soe_research/90
Additional URL
https://doi.org/10.1016/s0026-2714(99)00085-2