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A note on imprecise Monte Carlo over credal sets via importance sampling

Troffaes, Matthias C.M.

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Authors



Contributors

Alessandro Antonucci
Editor

Giorgio Corani
Editor

Inés Couso
Editor

Sébastien Destercke
Editor

Abstract

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.

Citation

Troffaes, M. C. (2017). A note on imprecise Monte Carlo over credal sets via importance sampling. In A. Antonucci, G. Corani, I. Couso, & S. Destercke (Eds.), Proceedings of the Tenth International Symposium on Imprecise Probability : Theories and Applications, 10-14 July 2017, Lugano (Switzerland) (325-332)

Conference Name The Tenth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA ’17)
Conference Location Lugano, Switzerland
Start Date Jul 10, 2017
End Date Jul 14, 2017
Acceptance Date Apr 17, 2017
Online Publication Date Jun 20, 2017
Publication Date Jun 20, 2017
Deposit Date Mar 9, 2017
Publicly Available Date Mar 29, 2024
Publisher PMLR
Pages 325-332
Series Title Proceedings of Machine Learning Research
Series Number 62
Series ISSN 1938-7228
Book Title Proceedings of the Tenth International Symposium on Imprecise Probability : Theories and Applications, 10-14 July 2017, Lugano (Switzerland).
Public URL https://durham-repository.worktribe.com/output/1147530
Publisher URL http://proceedings.mlr.press/v62/troffaes17a.html

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