Publication details for Matthias TroffaesTroffaes, Matthias C. M. (2017), A note on imprecise Monte Carlo over credal sets via importance sampling, in Antonucci, Alessandro, Corani, Giorgio, Couso, Inés & Destercke, Sébastien eds, Proceedings of Machine Learning Research 62: The Tenth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA ’17). Lugano, Switzerland, PMLR, 325-332.
- Publication type: Conference Paper
- ISSN/ISBN: 1938-7228
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
Other versions of this publication
- 2018: Imprecise Monte Carlo simulation and iterative importance sampling for the estimation of lower previsions (newer version)
This brief paper is an exploratory investigation of how we can apply sensitivity analysis over importance sampling weights in order to obtain sampling estimates of lower previsions described by a parametric family of distributions. We demonstrate our results on the imprecise Dirichlet model, where we can compare with the analytically exact solution. We discuss the computational limitations of the approach, and propose a simple iterative importance sampling method in order to overcome these limitations. We find that the proposed method works pretty well, at least in the example studied, and we discuss some further possible extensions.