Reliability Studies of the Log-Exponential Inverse Gaussian Distribution

In this article, we investigate the monotonicity of the density, failure rate, and mean residual life functions of the log-exponential inverse Gaussian distribution. It turns out that, in this case, the monotonicity of the density, failure rate, and mean residual life functions take different forms...

Full description

Saved in:
Bibliographic Details
Published in:Communications in statistics. Theory and methods 2009-01, Vol.38 (19), p.3532-3543
Main Authors: Ghitany, M. E., Al-Mutairi, D. K., Gupta, Ramesh C.
Format: Article
Language:English
Subjects:
Applications
Bathtub shaped
Critical points
Exact sciences and technology
Failure rate
General topics
Log-EIG distribution
Mathematical analysis
Mathematics
Mean residual life
Monotonicity
Primary 62N05
Probability and statistics
Probability theory and stochastic processes
Reliability, life testing, quality control
Sciences and techniques of general use
Secondary 62N02
Special functions
Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications)
Statistics
Upside-down bathtub shaped
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this article, we investigate the monotonicity of the density, failure rate, and mean residual life functions of the log-exponential inverse Gaussian distribution. It turns out that, in this case, the monotonicity of the density, failure rate, and mean residual life functions take different forms depending on the range of the parameters. Maximum likelihood estimators of the critical points of the density, failure rate, and mean residual life functions of the model are evaluated using Monte Carlo simulations. An example of a published data set is used to illustrate the estimation of the critical points.
ISSN:0361-0926
1532-415X
DOI:10.1080/03610920802601356