Parameter estimation from aggregate observations: a Wasserstein distance-based sequential Monte Carlo sampler

In this work, we study systems consisting of a group of moving particles. In such systems, often some important parameters are unknown and have to be estimated from observed data. Such parameter estimation problems can often be solved via a Bayesian inference framework. However, in many practical pr...

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Detalhes bibliográficos
Main Authors: Chen Cheng, Linjie Wen, Jinglai Li
Formato: Artigo
Idioma:English
Publicado em: The Royal Society 2023-08-01
Colecção:Royal Society Open Science
Assuntos:
Acesso em linha:https://royalsocietypublishing.org/doi/10.1098/rsos.230275