PAIRWISE LIKELIHOOD PROCEDURE FOR TWO-SAMPLE LOCATION PROBLEM.

This paper is about estimating shift parameter by using pairwise differences in the two-sample location problem, which assumes G(x)=F(x-Δ). The parameter Δ is called location shift parameter between populations of F(x) and G(x). Distribution and density functions of the pairwise differences can be found and used to construct a log likelihood function with respect to the shift parameter. An estimator of the shift parameter is found by Newton's one step algorithm from the log likelihood function. Asymptotic properties of the new estimator which is similar to a regular MLE estimator are shown under some regularity conditions. As an example, normal and Laplace Distribution model assumptions are investigated using the proposed approach. Moreover, a hypothesis testing procedure is developed and shown that pairwise difference approach is asymptotically equivalent to the Rao's score type likelihood test. [ABSTRACT FROM AUTHOR]