Progressive Type-II hybrid censoring is a mixture of pro- gressive Type-II and hybrid censoring schemes. In this pa- per, we discuss the statistical inference onWeibull parameters when the observed data are progressively Type-II hybrid cen- sored. We derive the maximum likelihood estimators (MLEs) and the approximate maximum likelihood estimators (AM- LEs) of the Weibull parameters. We then use the Asymp- totic distributions of the maximum likelihood estimators to construct approximate confidence intervals. Bayes estimates and the corresponding highest posterior density credible in- tervals of the unknown parameters are obtained under suit- able priors on the unknown parameters and also by using the Gibbs sampling procedure. Monte Carlo simulations are then performed for comparing the confidence intervals based on all those different methods. Finally, one data set is analyzed for illustrative purposes

Keywords