On the computation and some applications of multivariate isotonic regression

Multivariate isotonic regression theory plays a key role in the field of statistical inference under order restrictions for vector valued parameters. A Fortran program for the earlier proposed algorithm for the computation of multivariate isotonic regression is presented. The convergence of the algorithm is studied when the dimension is greater than or equal to five through Monte Carlo simulations. Two different types of numerical examples are given to illustrate the applications of multivariate isotonic regression.