Goodness-of-Fit Test Based on Kullback-Leibler Information for Progressively Type-II Censored Data

Author

Rad, Arezou Habibi ; Yousefzadeh, Fatemeh ; Balakrishnan, Narayanaswamy

Author_Institution

Dept. of Stat., Ferdowsi Univ. of Mashhad, Mashhad, Iran

Volume

60

Issue

3

fYear

2011

Firstpage

570

Lastpage

579

Abstract

We express the joint entropy of progressively Type-II censored order statistics in terms of an incomplete integral of the hazard function, and use it to develop a simple estimate of the joint entropy of progressively Type-II censored data, considered earlier by Balakrishnan , IEEE Trans. Reliability, vol. 56, pp. 349-356. We then construct a goodness-of-fit test statistic based on the Kullback-Leibler information for Pareto, log-normal, and Weibull distributions by using maximum likelihood estimates and approximate maximum likelihood estimates of the model parameters. Finally, we use Monte Carlo simulations to evaluate the power of the proposed test for several alternatives under different sample sizes and progressive censoring schemes.

Keywords

Monte Carlo methods; Pareto distribution; Weibull distribution; approximation theory; maximum likelihood estimation; Kullback-Leibler information; Monte Carlo simulations; Pareto distribution; Weibull distributions; approximate maximum likelihood estimates; goodness-of-fit test; hazard function; integral; progressively type-II censored data; Entropy; Hazards; Joints; Maximum likelihood estimation; Probability density function; Testing; Weibull distribution; Approximate maximum likelihood estimate; Kullback-Leibler information; Monte Carlo simulation; Pareto distribution; Weibull distribution; entropy; goodness-of-fit test; hazard function; log-normal distribution; maximum likelihood estimate; progressively type-II censored data;

fLanguage

English

Journal_Title

Reliability, IEEE Transactions on

Publisher

ieee

ISSN

0018-9529

Type

jour

DOI

10.1109/TR.2011.2162470

Filename

5970088