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Research Article Open access CC BY 4.0

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

Everestus O. Ossai, Mbanefo S. Madukaife

Asian Journal of Probability and Statistics · pp. 146–156 · Published 20 Dec 2022

10.9734/ajpas/2022/v20i4445

Abstract

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

Statistical manpower planning heterogeneity hidden Markov model number of states likelihood ratio test

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Cited by 3

An extended Markov-switching model approach to latent heterogeneity in departmentalized manpower systems

Everestus O. Ossai, Uchenna C. Nduka, Mbanefo S. Madukaife · Communications in Statistics - Theory and Methods · 2023

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