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Автор Dechert, W. D.
Автор O'Donnell, S. I.
Автор Brock, W. A.
Дата выпуска 2007
dc.description We present both analytical and numerical results for a model where the stochastic dynamical system is not fully known. We implement an optimal control solution for the problem that incorporates Bayes' learning of an unknown parameter in the model. The computational solution is for a model of phosphorus in a lake and we show that in that context full learning takes place. The model includes a Skiba-like point, and although the long run level of phosphorus in the lake is sensitive to initial conditions, learning is not.
Формат application.pdf
Издатель Taylor & Francis Group
Копирайт Copyright Taylor and Francis Group, LLC
Тема Bayesian learning
Тема Skiba
Тема Pollution
Тема Stochastic dynamic programming
Тема (62C10) Bayesian problem
Тема (90C15) Stochastic programming
Тема (93C55) Discrete-time systems
Тема (90C90) Applications of mathematical programming
Тема (91B76) Environmental economics (natural resource models, harvesting, pollution, etc.)
Название Bayes' learning of unknown parameters
Тип research-article
DOI 10.1080/10236190601069168
Electronic ISSN 1563-5120
Print ISSN 1023-6198
Журнал Journal of Difference Equations and Applications
Том 13
Первая страница 121
Последняя страница 133
Аффилиация Dechert, W. D.; Department of Economics, University of Wisconsin
Аффилиация O'Donnell, S. I.; Baylor College of Medicine, Children's Nutrition Research Center
Аффилиация Brock, W. A.; Department of Economics, University of Wisconsin
Выпуск 2-3
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