Please use this identifier to cite or link to this item: https://doi.org/10.1007/s11222-011-9300-x
Title: The ensemble Kalman filter is an ABC algorithm
Authors: Nott, D.J. 
Marshall, L.
Ngoc, T.M.
Keywords: Approximate Bayesian computation
Data assimilation
Ensemble Kalman filter
Regression adjustment
Issue Date: Nov-2012
Citation: Nott, D.J., Marshall, L., Ngoc, T.M. (2012-11). The ensemble Kalman filter is an ABC algorithm. Statistics and Computing 22 (6) : 1273-1276. ScholarBank@NUS Repository. https://doi.org/10.1007/s11222-011-9300-x
Abstract: The ensemble Kalman filter is the method of choice for many difficult high-dimensional filtering problems in meteorology, oceanography, hydrology and other fields. In this note we show that a common variant of the ensemble Kalman filter is an approximate Bayesian computation (ABC) algorithm. This is of interest for a number of reasons. First, the ensemble Kalman filter is an example of an ABC algorithm that predates the development of ABC algorithms. Second, the ensemble Kalman filter is used for very high-dimensional problems, whereas ABC methods are normally applied only in very low-dimensional problems. Third, recent state of the art extensions of the ensemble Kalman filter can also be understood within the ABC framework. © 2011 Springer Science+Business Media, LLC.
Source Title: Statistics and Computing
URI: http://scholarbank.nus.edu.sg/handle/10635/105416
ISSN: 09603174
DOI: 10.1007/s11222-011-9300-x
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