Simulation-based parameter estimation via a combination of embedded normalizing flows and implied empirical probabilities under moment restrictions
In this work, we present a simulation-based parameter estimation framework for a model defined by a computational simulation of a physical system. We specifically outline an estimation framework consisting of two closely-integrated steps that facilitate an overall end-to-end parameter estimation scheme. The first step involves utilizing an embedded normalizing flow which is used to transform the unknown complex distribution of the residual information into a simple base distribution corresponding to the transformed residual information. In the second step, an empirical-likelihood estimator, under moment restrictions, is utilized for imposing an indirect constrain on the base distribution,...
| Authors | Getachew K. Befekadu |
|---|---|
| Primary category | stat.ME |
| Published | 27 July 2026 |
| Last updated at source | 27 July 2026 |
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