Posterior analysis of the compound Rayleigh distribution under balanced loss functions for censored data

作者：Barot D R^*; Patel M N

来源：Communications in Statistics - Theory and Methods, 2017, 46(3): 1317-1336.

DOI：10.1080/03610926.2015.1019140

• Balanced symmetric and asymmetric loss functions
• Bayesian estimation
• Maximum likelihood estimation
• Monte Carlo simulation
• Posterior risk
• 62C12
• 62N01
• 62F10
• 62F15
• 62N05

This paper develops Bayesian analysis in the context of progressively Type II censored data from the compound Rayleigh distribution. The maximum likelihood and Bayes estimates along with associated posterior risks are derived for reliability performances under balanced loss functions by assuming continuous priors for parameters of the distribution. A practical example is used to illustrate the estimation methods. A simulation study has been carried out to compare the performance of estimates. The study indicates that Bayesian estimation should be preferred over maximum likelihood estimation. In Bayesian estimation, the balance general entropy loss function can be effectively employed for optimal decision-making.

• 出版日期2017