Importance Sampling for Logarithmic Pool Ensembles
Resumo
In this work, theoretical results and computational simulations are being developed for the use of Importance Sampling (IS) schemes in situations where the target distribution (πα(x)) can be expressed as proportional to a logarithmic combination of distributions (πk(x)’s). The objectives include determining the optimal proposals sets and bounds for the variances of the IS estimators when calculated using these proposal sets and comparing them to known proposal schemes. [...]
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Referências
L. M. Carvalho, D. A. M. Villela, F. C. Coelho, and L. S. Bastos. “Bayesian Inference for the Weights in Logarithmic Pooling”. In: Bayesian Analysis 18.1 (2023), pp. 223–251. DOI: 10.1214/22-BA1311.
R. T. Clemen and R. L. Winkler. “Combining Probability Distributions From Experts in Risk Analysis”. In: Risk Analysis 19.2 (1999), pp. 187–203. DOI: 10.1023/A:1006917509560.
V. Elvira, L. Martino, D. Luengo, and M. F. Bugallo. “Generalized Multiple Importance Sampling”. In: Statistical Science 34.1 (2019), pp. 129–155. DOI: 10.1214/18-STS668.
F. Llorente and L. Martino. Optimality in importance sampling: a gentle survey. 2025. arXiv: 2502.07396 [stat.CO].
A. O’Hagan, C. E. Buck, A. Daneshkhah, J. R. Eiser, P. H. Garthwaite, D. J. Jenkinson, J. E. Oakley, and T. Rakow. “Multiple Experts”. In: Uncertain Judgements: Eliciting Experts’ Probabilities. John Wiley Sons, Ltd, 2006. Chap. 9, pp. 179–192. isbn: 9780470033319. doi: 10.1002/0470033312.ch9.
A. Owen and Y. Zhou. “Safe and Effective Importance Sampling”. In: Journal of the American Statistical Association 95.449 (2000), pp. 135–143. doi: 10.1080/01621459.2000.10473909.
S. T. Tokdar and R. E. Kass. “Importance sampling: a review”. In: WIREs Comput. Stat. 2.1 (Jan. 2010), pp. 54–60. issn: 1939-5108. doi: 10.1002/wics.56.
