Approximate Laplace importance sampling for the estimation of expected Shannon information gain in high-dimensional Bayesian design for nonlinear models

Autor: Yiolanda Englezou, Timothy W. Waite, David C. Woods

Publikováno v: Englezou, Y, Waite, T & Woods, D C 2022, ' Approximate Laplace importance sampling for the estimation of expected Shannon information gain in high-dimensional Bayesian design for nonlinear models ', Statistics and Computing, vol. 32, 82 . https://doi.org/10.1007/s11222-022-10159-2

One of the major challenges in Bayesian optimal design is to approximate the expected utility function in an accurate and computationally efficient manner. We focus on Shannon information gain, one of the most widely used utilities when the experimen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b6179618a17a437fe3a9bc3632bb10a
https://eprints.soton.ac.uk/470495/

Designs for generalized linear models with random block effects via information matrix approximations

Autor: Timothy W. Waite, David C. Woods

Publikováno v: Biometrika. 102:677-693

The selection of optimal designs for generalized linear mixed models is complicated by the fact that the Fisher information matrix, on which most optimality criteria depend, is computationally expensive to evaluate. Our focus is on the design of expe

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1898ad2ff36d8ddabcab68d0db888b94
https://doi.org/10.1093/biomet/asv005