Discriminating Between Exponential and Lindley Distributions

Abstract

In literature, Lindley distribution is considered as an alternate to the exponential distribution. In the present work, a methodology is developed to discriminate between exponential and Lindley distributions based on the ratio of the maximum likelihoods. Asymptotic distribution of the test statistic under the null hypothesis is derived and the minimum sample size required to discriminate between the two distributions for a user specified probability of correct selection is obtained. Numerical illustrations of the methodology are given through simulated and real life data sets.

Discriminating among Generalized Exponential, Weighted Exponential and Weibull Distributions

“…Raqab et al [20] studied the discriminating problem of the WB, the log-normal, and the log-logistic distributions based on the RML and the MKD methods. Vaidyanathan and Varghese [21] applied the RML and the MKD methods to discriminate between the exponential and the Lindley distributions based on a given random sample of observations, and this has been widely used in the fields of biology and engineering. Recently, Paul et al [22] developed the SPRT methodology to discriminate between any two of the log-normal, the WB, and the log-logistic distributions as well as to discriminate among these distributions, which allowed the use of a less than average sample size without sacrificing the probability of correct selection (PCS).…”