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In this article, Burr type-XII distribution (BXIID) is employed to make one- and two-sample Bayesian prediction schemes for future order statistics and record values in case of adaptive progressive type-II censoring scheme (APTIICS). Real data set are presented as an application. Also, some numerical computations using simulated data from the underlying distribution in case of ATIIPCS are obtained. [ABSTRACT FROM AUTHOR]

In this paper, based on an adaptive Type-II progressively censored sample from the generalized exponential distribution, the maximum likelihood and Bayesian estimators are derived for the unknown parameters as well as the reliability and hazard functions. Also, the approximate confidence intervals of the unknown parameters, and the reliability and hazard functions are calculated. Markov chain Monte Carlo method is applied to carry out a Bayesian estimation procedure and in turn calculate the credible intervals. Moreover, results from simulation studies assessing the performance of our proposed method are included. Finally, an illustrative example using real data set is presented for illustrating all the inferential procedures developed here. [ABSTRACT FROM AUTHOR]

In this paper, for Weibull subfamily of Morgenstern family, the joint density of the concomitants of generalized order statistics (GOS 's) is used to obtain the maximum likelihood estimates (MLE) and Bayes estimates for the distribution parameters. Applications of these results for concomitants of order statistics are presented. [ABSTRACT FROM AUTHOR]