Predictive densities from the Rayleigh Life Model under Type II censored samples

Abstract

A tremendous amount of life data has been collected and analyzed in connection with recent advances in engineering and the biomedical sciences. It is desirable to make use of statistical and computational techniques that are at the cutting edge in order to reach valid conclusions about the nature of the underlying model. The Rayleigh distribution has been widely used for modelling life data and most studies on this distribution concentrate on inference about the parameters or on the reliability and hazard functions. This paper is concerned with predictive inference for future responses from a Rayleigh distribution given a type II censored sample by using the Bayesian approach. We are considering both one-parameter and two-parameter Rayleigh distributions. Predictive densities for future responses are derived with hyperparameters to obtain informative results about future responses.

Keywords and phrases:

• type II censored sample
• Rayleigh life model
• Bayesian approach
• posterior density
• predictive density