Bayesian inference using product of spacings function for Progressive hybrid Type-I censoring scheme

ABSTRACT

This article is devoted to the development of product of spacings estimator for a Progressive hybrid Type-I censoring scheme with binomial removals. The experimental units are assumed to follow inverse Lindley distribution. We propose a Bayes estimator of associated scale parameter based on the product of spacings function and simultaneously compare it with that obtained under a usual Bayesian estimation procedure. The estimators are obtained under the squared error loss function along with corresponding HP intervals evaluated by using the Markov chain Monte-Carlo technique. The classical product of spacings estimator has also been derived and compared with the maximum likelihood estimator in addition to 95% average asymptotic confidence intervals. The applicability of the proposed methods is demonstrated by analysing a real data of guinea pigs affected with tuberculosis for the considered censoring scheme.

KEYWORDS:

• Expected total time to test
• inverse Lindley distribution
• maximum product of spacing
• Progressive hybrid Type-I censoring with binomial removals

AMS Subject Classification:

• 62Nxx
• 62Fxx

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 All numerical computations of this article are performed with R programming language.