Introduction to Imprecise Probabilities
(2014)
Book
Augustin, T., Coolen, F. P., De Cooman, G., & Troffaes, M. C. (Eds.). (2014). Introduction to Imprecise Probabilities. Wiley
Outputs (8)
Computation (2014)
Book Chapter
Troffaes, M. C., & Hable, R. (2014). Computation. In T. Augustin, F. P. Coolen, G. De Cooman, & M. C. Troffaes (Eds.), Introduction to Imprecise Probabilities (329-337). Wiley. https://doi.org/10.1002/9781118763117.ch16
Decision making (2014)
Book Chapter
Huntley, N., Hable, R., & Troffaes, M. C. (2014). Decision making. In T. Augustin, F. P. Coolen, G. de Cooman, & M. C. Troffaes (Eds.), Introduction to Imprecise Probabilities (190-206). Wiley. https://doi.org/10.1002/9781118763117.ch8
A geometric and game-theoretic study of the conjunction of possibility measures (2014)
Journal Article
Miranda, E., Troffaes, M. C., & Destercke, S. (2015). A geometric and game-theoretic study of the conjunction of possibility measures. Information Sciences, 298, 373-389. https://doi.org/10.1016/j.ins.2014.10.067In this paper, we study the conjunction of possibility measures when they are interpreted as coherent upper probabilities, that is, as upper bounds for some set of probability measures. We identify conditions under which the minimum of two possibilit... Read More about A geometric and game-theoretic study of the conjunction of possibility measures.
A Comparison of Real Time Thermal Rating Systems in the U.S. and the UK (2014)
Journal Article
Greenwood, D. M., Gentle, J. P., Myers, K. S., Davison, P. J., West, I. J., Bush, J. W., …Troffaes, M. C. (2014). A Comparison of Real Time Thermal Rating Systems in the U.S. and the UK. IEEE Transactions on Power Delivery, 29(4), 1849-1858. https://doi.org/10.1109/tpwrd.2014.2299068Real-Time Thermal Rating is a smart grid technology that allows the rating of electrical conductors to be increased based on local weather conditions. Overhead lines are conventionally given a conservative, constant seasonal rating based on seasonal... Read More about A Comparison of Real Time Thermal Rating Systems in the U.S. and the UK.
A Note on Learning Dependence Under Severe Uncertainty (2014)
Conference Proceeding
Troffaes, M. C., Coolen, F. P., & Destercke, S. (2014). A Note on Learning Dependence Under Severe Uncertainty. 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 (498-507). https://doi.org/10.1007/978-3-319-08852-5_51We propose two models, one continuous and one categorical, to learn about dependence between two random variables, given only limited joint observations, but assuming that the marginals are precisely known. The continuous model focuses on the Gaussia... Read More about A Note on Learning Dependence Under Severe Uncertainty.
Multinomial logistic regression on Markov chains for crop rotation modelling (2014)
Conference Proceeding
Paton, L., Troffaes, M. C., Boatman, N., Hussein, M., & Hart, A. (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 (476-485). https://doi.org/10.1007/978-3-319-08852-5_49Often, 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 ch... Read More about Multinomial logistic regression on Markov chains for crop rotation modelling.
Lower previsions. (2014)
Book
Troffaes, M. C., & De Cooman, G. (2014). Lower previsions. Wiley