Reliability Estimation Of Stress Strength Model Based On Inverse Xgamma Distribution

The reliability of stress strength model is an important problem in reliability analysis.In this paper,two estimation methods are used to approximate the reliability of stress strength model with inverse xgamma distribution.Assuming that the stress random variable and strength random variable obeying the inverse xgamma distribution are independent of each other,the expression of reliability is obtained by calculation Based on the maximum likelihood principle,the first partial derivative of log likelihood function is iterated by Newton Raphson algorithm under complete data,and the point estimation and interval estimation of reliability are obtained On the other hand,the point estimation and interval estimation of reliability under progressive type II censored data are obtained by the same method Similarly,the Bayes estimation of parameters is obtained by Lindley algorithm and MCMC algorithm based on Bayes method under complete data and progressive type II censored data From the asymptotic normality of Bayes estimation,the asymptotic confidence interval of Lindley algorithm reliability and the maximum a posteriori probability density(HPD)interval of MCMC algorithm reliability are obtained.Finally,the maximum likelihood estimation and Bayes estimation methods are simulated under complete data and progressive II censored data,and the results are remarkable For example verification,the repair time samples of airborne communication transceiver are used to verify the effects of the two methods under complete data;It is verified by single carbon fiber sample under the progressive type II censored data.