Estimation of Inverse Lindley Distribution Using Product of Spacings Function for Hybrid Censored Data

This article presents different estimation procedure for inverse Lindley distribution for Type-I hybrid censored data. We have obtained the parameter estimate under both the classical and Bayesian paradigm. In the classical set up, method of Maximum Likelihood(ML) and Maximum Product of spacings (MP...

Full description

Saved in:
Bibliographic Details
Published in:Methodology and computing in applied probability 2019-12, Vol.21 (4), p.1377-1394
Main Authors: Basu, Suparna, Singh, Sanjay K., Singh, Umesh
Format: Article
Language:English
Subjects:
Bayesian analysis
Business and Management
Censored data (mathematics)
Computer simulation
Confidence intervals
Economics
Electrical Engineering
Guinea pigs
Life Sciences
Markov chains
Mathematics and Statistics
Monte Carlo simulation
Parameter estimation
Statistics
Tuberculosis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This article presents different estimation procedure for inverse Lindley distribution for Type-I hybrid censored data. We have obtained the parameter estimate under both the classical and Bayesian paradigm. In the classical set up, method of Maximum Likelihood(ML) and Maximum Product of spacings (MPS) estimates are obtained along with 95% asymptotic confidence interval. Bayesian estimation is implemented under the assumption of squared error loss function. An alternative Bayesian procedure is also proposed by incorporating the sample information through the spacings function instead of likelihood function. The Bayes estimates are computed using Markov Chain Monte Carlo (MCMC) technique due to their implicit nature. Highest posterior density (HPD) intervals based on these MCMC samples are evaluated and compared in terms of simulated risks. Further, a real data of 72 guinea pigs, infected with tuberculosis is analysed to justify the suitability of the afore-said estimation techniques under the specified censoring scheme.
ISSN:1387-5841
1573-7713
DOI:10.1007/s11009-018-9676-6