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Multinomial logistic regression on Markov chains for crop rotation modelling.

Paton, Lewis and Troffaes, Matthias C. M. and Boatman, Nigel and Hussein, Mohamud and Hart, Andy (2014) 'Multinomial logistic regression on Markov chains for crop rotation modelling.', in Information processing and management of uncertainty in knowledge-based systems : 15th International Conference, IPMU 2014, Montpellier, France, July 15-19, 2014 ; proceedings, part III. , pp. 476-485. Communications in computer and information science. (444).


Often, in dynamical systems such as farmer’s crop choices, the dynamics are driven by external non-stationary factors, such as rainfall, temperature and agricultural input and output prices. Such dynamics can be modelled by a non-stationary Markov chain, where the transition probabilities are multinomial logistic functions of such external factors. We extend previous work to investigate the problem of estimating the parameters of the multinomial logistic model from data. We use conjugate analysis with a fairly broad class of priors, to accommodate scarcity of data and lack of strong prior expert opinion. We discuss the computation of bounds for the posterior transition probabilities. We use the model to analyse some scenarios for future crop growth.

Item Type:Book chapter
Full text:Publisher-imposed embargo
(AM) Accepted Manuscript
File format - PDF (Copyright agreement prohibits open access to the full-text)
Publisher Web site:
Date accepted:No date available
Date deposited:16 October 2014
Date of first online publication:July 2014
Date first made open access:No date available

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