ARTICLE TITLE

AUTHOR NAME; V. Adah; J. A. Ikughur; S. C. Nwaosu; E. F. Udoumoh

doi:10.64497/jssci.137

Authors

V. Adah Department of Statistics, Joseph Sarwuan Tarka University, Makurdi, Nigeria
J. A. Ikughur Department of Statistics, Joseph Sarwuan Tarka University, Makurdi, Nigeria
S. C. Nwaosu Department of Statistics, Joseph Sarwuan Tarka University, Makurdi, Nigeria
E. F. Udoumoh Department of Statistics, Joseph Sarwuan Tarka University, Makurdi, Nigeria

DOI:

https://doi.org/10.64497/jssci.137

Abstract

In this study, Bayesian estimation procedure is presented especially for a binary Markov chain model under the assumption that the prior for had non- informative and informative prior distribution when the number of unfavourable climatic periods for the growth of the crop is more than the favourable period. Thus, a sequence of logical connectives was used to combine climatic variable namely , rainfall and temperature to obtain favourable and unfavourable crop growth conditions for the Pearl millet. Bayed factor revealed the that probability estimates obtained using the informative prior performed better than those obtained using the non-informative prior. There is a lower probability, 0.4227 of a favourable climate for the pearl millet growth, indicating that climate change has an adverse effect on the crop.

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References

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