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

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...

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Bibliographic Details
Main Authors: Hiroaki Inoue, Koji Hukushima, Toshiaki Omori
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Entropy
Subjects:
state space model
probabilistic graphical model
replica exchange particle Metropolis–Hastings method
replica exchange method
particle Metropolis–Hastings method
particle Markov chain Monte Carlo method
Online Access:https://www.mdpi.com/1099-4300/24/1/115

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https://www.mdpi.com/1099-4300/24/1/115

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