Estimation for the three-parameter gamma distribution based on progressively censored data

Indrani Basak, N. Balakrishnan

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Some work has been done in the past on the estimation for the three-parameter gamma distribution based on complete and censored samples. In this paper, we develop estimation methods based on progressively Type-II censored samples from a three-parameter gamma distribution. In particular, we develop some iterative methods for the determination of the maximum likelihood estimates (MLEs) of all three parameters. It is shown that the proposed iterative scheme converges to the MLEs. In this context, we propose another method of estimation which is based on missing information principle and moment estimators. Simple alternatives to the above two methods are also suggested. The proposed estimation methods are then illustrated with a numerical example. We also consider the interval estimation based on large-sample theory and examine the actual coverage probabilities of these confidence intervals in case of small samples using a Monte Carlo simulation study.

Original languageEnglish (US)
Pages (from-to)305-319
Number of pages15
JournalStatistical Methodology
Volume9
Issue number3
DOIs
StatePublished - May 1 2012

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

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