Everestus O. Ossai

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 · 2022

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 li...

Open access Research Article 10.9734/ajpas/2022/v20i4445

Homogeneity versus Parsimony in Markov Manpower Models: A Hidden Markov Chain Approach

Everestus O. Ossai, Precious N. Ezra, Felix O. Ohanuba & Martin N. Eze · Asian Journal of Probability and Statistics · 2022

We aim at tackling the problem of inadequate specification of a Markov manpower model in this paper, by formulating a procedure for validating the inclusion or non-inclusion of some transition parameters in the model. The mover-stayer principle and its extensions are employed to...

Open access Research Article 10.9734/ajpas/2022/v20i4441