چکیده:
Statistical prediction analysis plays an important role in a wide
range of fields. Examples include engineering systems, design of experiments,
etc. In this paper, based on progressively Type-II right censored data,
Bayesian two-sample point and interval predictors are developed under both
informative and non-informative priors. By assuming a generalized exponential
model, prediction bounds as well as Bayes point predictors are obtained
under the squared error loss (SEL) and the Linear-Exponential (LINEX) loss
functions for the order statistic in a future progressively Type-II censored
sample with an arbitrary progressive censoring scheme. The derived results
may be used for prediction of total time on test in lifetime experiments. In
addition to numerical method, Gibbs sampling procedure (as Markov Chain
Monte Carlo method) are used to assess approximate prediction bounds and
Bayes point predictors under the SEL and LINEX loss functions. The performance
of the proposed prediction procedures are also demonstrated via a
Monte Carlo simulation study and an illustrative example, for each method.