On the probabilities of rankings of k populations with applications

The method of approximating a continuous distribution by a discrete distribution is used to approximate certain multidimensional ranking integrals. in the location and scale parameter cases the method results in a simple iterative counting algorithm. a bound on the error term is given. the algorithm is applied to the problem of completely ranking normal means and shown to be quite accurate and fast. applications of the above complete ranking problem are given, and the results are used to compute upper confidence bounds for mean differences in a trend situation. 1977, Taylor & Francis Group, LLC. All rights reserved.

On the probabilities of rankings of k populations with applications Academic Article