Estimations of the parameters for modified Weibull distribution under adaptive type-II progressive censored samples
نویسندگان
1 Department of Statistics, Imam Khomeini International University, Qazvin, Iran
2 Department of Statistics, Imam Khomeini International University, Qazvin, Iran
doi
10.22034/jsmta.2024.20261.1102چکیده
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.