estimations of the parameters for modified weibull distribution under adaptive type-ii progressive censored samples

This paper describes the point and interval estimation of the unknown parameters of modified weibull distribution under the adaptive type-ii progressive censored samples‎. ‎first‎, ‎we obtain the maximum likelihood estimation of parameters‎. ‎because maximum likelihood estimations should be solved in numerical methods and cannot be derived in a closed form‎, ‎the approximate maximum likelihood estimations of the parameters are achieved‎. ‎also‎, ‎asymptotic confidence intervals are obtained by earning the asymptotic distribution of the parameters‎. ‎moreover‎, ‎two bootstrap confidence intervals are derived‎. ‎second‎, ‎the bayesian estimation of parameters is approximated using the markov chain monte carlo algorithm and lindley's method‎. ‎furthermore‎, ‎the highest posterior density credible intervals of the parameters are derived‎. ‎finally‎, ‎the different proposed estimations have been compared by the simulation studies and one data set is analyzed to illustrative aims.