Abstract
A continuous life distribution function f with f(x)=0 for x ≶ is said to be increasing failure rate average (IFRA) if and only if and all x For testing the null hypothesis that f is an exponentia distribution versus the alternative hypothesis that f is a nonexponential IFRA distribution DESHPANDE [BIometrika 70 (1983): 514:518] proposed a class of testing which depends on b the choice of b has been crucial since than In this paper we propose a new measure of IFRA ness that is independent of b and we use it to test whether one destribution is more IFRA than other. The Properties of the test such as unbiasedness, consistency and asymptotic normality are dscussed.Monte Carolo estimates of power are obtained for small sample sizes. Large sample performance is measured in terms of Asymptotic relative efficiency with respect to Tiwri and ZALKIAr,s (1988) test.
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