Title :
Testing exponentiality based on the Kullback-Leibler information with the type II censored data
Author_Institution :
Dept. of Appl. Stat., Yonsei Univ., Seoul, South Korea
fDate :
3/1/2005 12:00:00 AM
Abstract :
We express the joint entropy of order statistics in terms of an incomplete integral of the hazard function, and provide a simple estimate of the joint entropy of the type II censored data. Then we establish a goodness of fit test statistic based on the Kullback-Leibler information with the type II censored data, and compare its performance with some leading test statistics. A Monte Carlo simulation study shows that the proposed test statistic shows better powers than some leading test statistics against the alternatives with monotone increasing hazard functions.
Keywords :
Monte Carlo methods; maximum entropy methods; reliability theory; Kullback-Leibler information; Monte Carlo simulation; exponentiality testing; goodness of fit test statistic; hazard function; joint entropy; maximum entropy; order statistics; type II censored data; Density functional theory; Distribution functions; Entropy; Hazards; Performance evaluation; Random variables; Statistical analysis; Statistical distributions; Statistics; Testing; Entropy; Monte-Carlo simulation; hazard function; maximum entropy; order statistics;
Journal_Title :
Reliability, IEEE Transactions on
DOI :
10.1109/TR.2004.837314