On Selecting the Best Population among Increasing Failure Rate Average Populations

Abstract

One of the important areas of research in Statistical Inference, namely, the selection and ranking of populations is well attended by many researchers. Here, a selection procedure is developed to select the population possessing stronger increasing failure rate average (IFRA) property among the several IFRA populations. A selection procedure is developed using a measure of departure from exponentiality towards IFRA. The strength of IFRA property of populations is determined by considering the measure given by Keerthi and Pandit [8]. The statistic proposed by Keerthi and Pandit [8] to test exponentiality against IFRA alternatives is based on a U-statistic with a kernel of degree four. Keerthi and Pandit [8] established the large sample properties of the statistic which is the basis for selection procedure. Also the performance of the selection procedure is evaluated using probability of correct selection.