Publication details for Matthias TroffaesTroffaes, Matthias C. M., Coolen, Frank P. A. & Destercke, Sebastien (2014), A Note on Learning Dependence Under Severe Uncertainty, Communications in Computer and Information Science 444: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Montpellier, France, Springer, Montpellier, 498-507.
- Publication type: Conference Paper
- ISSN/ISBN: 1865-0929 (print), 1865-0937 (electronic), 9783319088518 (print), 9783319088525 (electronic)
- DOI: 10.1007/978-3-319-08852-5_51
- Keywords: Bivariate data, Categorical data, Copula, Gaussian copula, Robust Bayesian, Imprecise probability.
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
We 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 Gaussian case, while the categorical model is generic. We illustrate the resulting statistical inferences on a simple example concerning the body mass index. Both methods can be extended easily to three or more random variables.
15th International Conference, IPMU 2014, Montpellier, France, July 15-19, 2014.