BibTeX

@article{2209.11057v1,
Author        = {Florent Leclercq},
Title         = {Simulation-based inference of Bayesian hierarchical models while
  checking for model misspecification},
Eprint        = {2209.11057v1},
DOI           = {10.3390/psf2022005004},
ArchivePrefix = {arXiv},
PrimaryClass  = {stat.ME},
Abstract      = {This paper presents recent methodological advances to perform
simulation-based inference (SBI) of a general class of Bayesian hierarchical
models (BHMs), while checking for model misspecification. Our approach is based
on a two-step framework. First, the latent function that appears as second
layer of the BHM is inferred and used to diagnose possible model
misspecification. Second, target parameters of the trusted model are inferred
via SBI. Simulations used in the first step are recycled for score compression,
which is necessary to the second step. As a proof of concept, we apply our
framework to a prey-predator model built upon the Lotka-Volterra equations and
involving complex observational processes.},
Year          = {2022},
Month         = {Sep},
Note          = {Physical Sciences Forum 2022, 5, 4},
Url           = {http://arxiv.org/abs/2209.11057v1},
File          = {2209.11057v1.pdf}
}