Estimation using hybrid censored data from a two-parameter distribution with bathtub shape

Authors:
Manoj Kumar Rastogi;Yogesh Mani Tripathi
Affiliations:
-;-
Venue:
Computational Statistics & Data Analysis
Year:
2013

Citing 4
Cited 0

Estimation of parameters from progressively censored data using EM algorithm

Computational Statistics & Data Analysis
Analysis of Type-II progressively hybrid censored data

Computational Statistics & Data Analysis
Bayesian survival estimation of Pareto distribution of the second kind based on failure-censored data

Computational Statistics & Data Analysis
Hybrid censoring: Models, inferential results and applications

Computational Statistics & Data Analysis

Quantified Score

Hi-index	0.03

Visualization

Abstract

The problem of estimating unknown parameters of a two-parameter distribution with bathtub shape is considered under the assumption that samples are hybrid censored. The maximum likelihood estimates are obtained using an EM algorithm. The Fisher information matrix is obtained as well and the asymptotic confidence intervals are constructed. Further, two bootstrap interval estimates are also proposed for the unknown parameters. Bayes estimates are evaluated under squared error loss function. Approximate explicit expressions for these estimates are derived using the Lindley method as well as using the Tierney and Kadane method. An importance sampling scheme is then proposed to generate Markov Chain Monte Carlo samples which have been used to compute approximate Bayes estimates and credible intervals for the unknowns. A numerical study is performed to compare the proposed estimates. Finally, two data sets are analyzed for illustrative purposes.