Parameter estimation of linear exponential distribution under type-Ⅱ doubly censored sample
The maximum likelihood estimation and Bayes estimation of unknown parameters in linear exponential distri-bution are discussed under the type-Ⅱ doubly censored sample.The maximum likelihood estimation of unknown parameter is obtained by Newton-Raphson iterative method,and the unique existence of maximum likelihood estimation is proved.The Bayes approximate estimates of the parameters are discussed by Tierney-Kadane approximation under symmetric loss function and asymmetric loss function by selecting non-informative prior distribution and conjugate prior distribution.The mean square error of maximum likelihood estimation and Bayes estimation of unknown parameters is simulated by MatlabR200b.The re-sults show that the mean square error of Bayes estimation of unknown parameters is the smallest when the Gamma prior distri-bution is selected and the squared loss function is used under different sample sizes and different censored schemes.
万方数据
维普
