Mixtures of skewed Kalman filters Academic Article uri icon

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. 2013 Elsevier Inc.

published proceedings

  • JOURNAL OF MULTIVARIATE ANALYSIS

author list (cited authors)

  • Kim, H., Ryu, D., Mallick, B. K., & Genton, M. G.

citation count

  • 9

complete list of authors

  • Kim, Hyoung-Moon||Ryu, Duchwan||Mallick, Bani K||Genton, Marc G

publication date

  • January 2014