Improved estimators of hazard rate from a selected exponential population

Abstract

Consider $k(\ge 2)$ number of independent populations, following two parameter exponential distributions, sharing a common location parameter and unequal scale parameters. The location and scale parameters are assumed to be unknown. We focus into the study of estimation of the hazard rate of a selected population with respect to entropy loss function. Define $W_i=Z_i-Y$, where $Z_i$ denotes the sample mean of the i-th sample and Y represents the minimum observation of all the samples, for $i=1,\dots ,k.$ We select the population with the largest $W_i$. In order to obtain improved estimator, Brewster-Zidek technique is implemented. Further, dominating estimators upon the improved ones are obtained using differential inequality approach. A numerical study of the risk improvements for the proposed estimators has been carried out.

KEYWORDS:

• Rao-Blackwellization
• hazard rate
• differential inequality approach
• entropy loss function
• Brewster-Zidek technique

Conflict Of Interest Statement

The authors proclaim that they do not have any conflict of interest.

Disclosure Statement

The authors declare that they don’t have any relevant financial or non financial competing interests.