Generalized Mixtures of Gamma and Exponentials and Reliability Properties of the Maximum from Friday and Patil Bivariate Exponential Model
- 9 August 2007
- journal article
- research article
- Published by Taylor & Francis in Communications in Statistics - Theory and Methods
- Vol. 36 (11) , 2011-2025
- https://doi.org/10.1080/03610920601143576
Abstract
The minimum and maximum order statistics from many of the common bivariate exponential distributions are predominantly generalized mixtures of exponentials; however, the maximum from the Friday and Patil bivariate exponential (FPBVE) model is either a generalized mixture of three or fewer exponentials or a generalized mixture of gamma and exponentials. In this article, we obtain conditions based on the weights and parameters of the generalized mixtures of gamma and one or two exponential distributions that yield legitimate probability models. Furthermore, we analyze properties of the failure rate of the maximum from the FPBVE model. This answers a question raised in Baggs and Nagaraja ( 1996 Baggs , G. E. , Nagaraja , H. N. ( 1996 ). Reliability properties of order statistics from bivariate exponential distributions . Commun. Statist. Stochastic Mod. 12 : 611 – 631 . [Taylor & Francis Online] [Google Scholar] ).Keywords
This publication has 13 references indexed in Scilit:
- Log-concavity of the extremes from Gumbel bivariate exponential distributionsStatistics, 2006
- Log-concave probability and its applicationsEconomic Theory, 2005
- RELIABILITY PROPERTIES OF SERIES AND PARALLEL SYSTEMS FROM BIVARIATE EXPONENTIAL MODELSCommunications in Statistics - Theory and Methods, 2002
- DETERMINATION OF CHANGE POINTS OF NON-MONOTONIC FAILURE RATESCommunications in Statistics - Theory and Methods, 2001
- Failure rate of the minimum and maximum of a multivariate normal distributionMetrika, 2001
- Continuous Multivariate DistributionsWiley Series in Probability and Statistics, 2000
- Reliability properties of order statistics from bivariate exponential distributionsCommunications in Statistics. Stochastic Models, 1996
- A Continuous Bivariate Exponential ExtensionJournal of the American Statistical Association, 1974
- Sufficient Conditions for a Mixture of Exponentials to be a Probability Density FunctionThe Annals of Mathematical Statistics, 1969
- A Bivariate Extension of the Exponential DistributionJournal of the American Statistical Association, 1961