Mixtures of skewed Kalman filters

Hyoung-Moon Kim, Duchwan Ryu, Bani K. Mallick and Marc G. Genton

Journal of Multivariate Analysis, 2014, vol. 123, issue C, 228-251

Abstract: Normal state-space models are prevalent, but to increase the applicability of the Kalman filter, we propose mixtures of skewed, and extended skewed, Kalman filters. To do so, the closed skew-normal distribution is extended to a scale mixture class of closed skew-normal distributions. Some basic properties are derived and a class of closed skew-t distributions is obtained. Our suggested family of distributions is skewed and has heavy tails too, so it is appropriate for robust analysis. Our proposed special sequential Monte Carlo methods use a random mixture of the closed skew-normal distributions to approximate a target distribution. Hence it is possible to handle skewed and heavy tailed data simultaneously. These methods are illustrated with numerical experiments.

Keywords: Closed skew-normal distribution; Discrete mixture; Kalman filter; Scale mixtures; Sequential importance sampling; Closed skew-t distribution (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.jmva.2013.09.002

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