Sequential Monte Carlo sampling for state space models

Mario V Wüthrich

The aim of these notes is to revisit sequential Monte Carlo (SMC) sampling. SMC sampling is a powerful simulation tool for solving non-linear and/or non-Gaussian state space models. We illustrate this with several examples.

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Year of publication:	[2017]
Authors:	Wüthrich, Mario V.
Published in:	Robustness in econometrics. - Cham : Springer, ISBN 978-3-319-50741-5. - 2017, p. 25-50
Subject:	Kalman Filter \| Transition System \| State Space Model \| Stochastic Volatility \| Importance Weight \| Zustandsraummodell \| State space model \| Monte-Carlo-Simulation \| Monte Carlo simulation \| Zeitreihenanalyse \| Time series analysis \| Stichprobenerhebung \| Sampling \| Stochastischer Prozess \| Stochastic process \| Volatilität \| Volatility \| Schätztheorie \| Estimation theory

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Type of publication:	Article
Type of publication (narrower categories):	Aufsatz im Buch ; Book section
Language:	English
Other identifiers:	10.1007/978-3-319-50742-2_2 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10011800920