Abstract
A Monte Carlo method for nonlinear non-Gaussian filtering and smoothing and its application to self-organising state-space models are shown in this paper.
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© 2001 Springer Science+Business Media New York
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Kitagawa, G., Sato, S. (2001). Monte Carlo Smoothing and Self-Organising State-Space Model. In: Doucet, A., de Freitas, N., Gordon, N. (eds) Sequential Monte Carlo Methods in Practice. Statistics for Engineering and Information Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-3437-9_9
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DOI: https://doi.org/10.1007/978-1-4757-3437-9_9
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-2887-0
Online ISBN: 978-1-4757-3437-9
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