Professor Matthias Troffaes matthias.troffaes@durham.ac.uk
Professor
Logistic Regression on Markov Chains for Crop Rotation Modelling
Troffaes, Matthias C.M.; Paton, Lewis
Authors
Lewis Paton
Contributors
Fabio Cozman
Editor
Thierry Denoeux
Editor
Sebastien Destercke
Editor
Teddy Seidenfeld
Editor
Abstract
Often, in dynamical systems, such as farmer's crop choices, the dynamics is driven by external non-stationary factors, such as rainfall, temperature, and economy. Such dynamics can be modelled by a non-stationary Markov chain, where the transition probabilities are logistic functions of such external factors. We investigate the problem of estimating the parameters of the logistic model from data, using conjugate analysis with a fairly broad class of priors, to accommodate scarcity of data and lack of strong prior expert opinions. We show how maximum likelihood methods can be used to get bounds on the posterior mode of the parameters.
Citation
Troffaes, M. C., & Paton, L. (2013). Logistic Regression on Markov Chains for Crop Rotation Modelling. In F. Cozman, T. Denoeux, S. Destercke, & T. Seidenfeld (Eds.), ISIPTA ’13 : proceedings of the eighth international symposium on imprecise probability : theories and applications July 2-5 2013, Compiègne, France (329-336)
Conference Name | ISIPTA'13: Proceedings of the Eighth International Symposium on Imprecise Probability: Theories and Applications |
---|---|
Conference Location | Compiegne, France |
Publication Date | Jul 5, 2013 |
Deposit Date | May 29, 2013 |
Publicly Available Date | Mar 28, 2024 |
Pages | 329-336 |
Book Title | ISIPTA ’13 : proceedings of the eighth international symposium on imprecise probability : theories and applications July 2-5 2013, Compiègne, France. |
Keywords | Logistic regression, Markov chain, Robust Bayesian, Conjugate, Maximum likelihood, Crop. |
Public URL | https://durham-repository.worktribe.com/output/1155709 |
Publisher URL | http://www.sipta.org/isipta13/index.php?id=paper&paper=033.html |
Files
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