Likelihood Ratio Search Procedure for Optimum Number of States in a Hidden Markov Manpower Model

This paper aims at obtaining the optimum number of states for a hidden Markov manpower model, which, hitherto, has been chosen arbitrarily. A search procedure that attains this after few steps across series N models is proposed. The likelihood ratio statistic employed to conduct pairwise model comparison tests on ordered according their level parsimony. illustration shows usefulness in choosing right avoid wrong specification such models. proposed can be useful other areas research, as biological, medical and social sciences, where application may require determination based unobserved data with latent heterogeneity. straightforward formulation its requires mainly adaptation specifications new area’s system dynamics.