Estimating Distributions of Parameters in Nonlinear State Space Models with Replica Exchange Particle Marginal Metropolis–Hastings Method

Extracting latent nonlinear dynamics from observed time-series data is important for understanding a dynamic system against the background of the observed data. A state space model is a probabilistic graphical model for time-series data, which describes the probabilistic dependence between latent va...

Descripción completa

Detalles Bibliográficos
Autores principales: Inoue, Hiroaki, Hukushima, Koji, Omori, Toshiaki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8774595/
https://www.ncbi.nlm.nih.gov/pubmed/35052141
http://dx.doi.org/10.3390/e24010115

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8774595/
https://www.ncbi.nlm.nih.gov/pubmed/35052141
http://dx.doi.org/10.3390/e24010115

Ejemplares similares