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Bayesian inference for the generalized exponential distribution
Abstract:The two-parameter generalized exponential (GE) distribution was introduced by Gupta and Kundu Gupta, R.D. and Kundu, D., 1999, Generalized exponential distribution. Australian and New Zealand Journal of Statistics, 41(2), 173–188.]. It was observed that the GE can be used in situations where a skewed distribution for a nonnegative random variable is needed. In this article, the Bayesian estimation and prediction for the GE distribution, using informative priors, have been considered. Importance sampling is used to estimate the parameters, as well as the reliability function, and the Gibbs and Metropolis samplers data sets are used to predict the behavior of further observations from the distribution. Two data sets are used to illustrate the Bayesian procedure.
Keywords:Generalized exponential distribution  Bayesian estimation  Bayesian prediction  Gibbs and Metropolis sampling  Importance sampling  Life testing
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