Statistical Inference for Lindley Model based on Type II Censored Data

DOI

10.2991/jsta.2017.16.2.4How to use a DOI?

Keywords

Lindley model; Type II censoring; Maximum likelihood estimator; Bayes estimator; Importance Sampling.

Abstract

In this paper, the moment-based, maximum likelihood and Bayes estimators for the unknown parameter of the Lindley model based on Type II censored data are discussed. The expectation maximization (EM) algorithm and direct maximization methods are used to obtained the maximum likelihood estimator (MLE). Existence and uniqueness of the moment-based and maximum likelihood estimators are discussed and a bias corrected estimator based on parametric bootstrap is developed. For Bayesian estimation, since the Bayes estimator cannot be obtained in an explicit form, two approximations based on Lindley and the importance sampling methods are used. Asymptotic confidence intervals, bootstrap confidence intervals and credible intervals are also proposed. Based on Type II censored data, the prediction of future observations is discussed. The analysis of a real data has been presented for illustrative purposes. Finally, Monte Carlo simulations are performed to compare the performances of the proposed estimation methods.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - A. Asgharzadeh
AU  - H.K.T. Ng
AU  - R. Valiollahi
AU  - M. Azizpour
PY  - 2017
DA  - 2017/06/01
TI  - Statistical Inference for Lindley Model based on Type II Censored Data
JO  - Journal of Statistical Theory and Applications
SP  - 178
EP  - 197
VL  - 16
IS  - 2
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.2017.16.2.4
DO  - 10.2991/jsta.2017.16.2.4
ID  - Asgharzadeh2017
ER  -