Variational Iterations for Filtering and Smoothing with skew-t measurement noise
2015 (English)Report (Other academic)
In this technical report, some derivations for the filter and smoother proposed in  are presented. More specifically, the derivations for the cyclic iteration needed to solve the variational Bayes filter and smoother for state space models with skew t likelihood proposed in  are presented.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. , 9 p.
LiTH-ISY-R, ISSN 1400-3902 ; 3083
skew t-distribution, skewness, t-distribution, robust filtering, Kalman filter, RTS smoother, variational Bayes
IdentifiersURN: urn:nbn:se:liu:diva-115741ISRN: LiTH-ISY-R-3083OAI: oai:DiVA.org:liu-115741DiVA: diva2:797463
FunderSwedish Research Council, 621-2010-4301
The technical report is related to the paper:
 H. Nurminen, T. Ardeshiri, R. Piché, and F. Gustafsson, “Robust inference for state-space models with skewed measurement noise,” submitted to Signal Processing Letters, 2015, [Online]. Available: http://arxiv.org/abs/1503.066062015-03-242015-03-182015-04-07Bibliographically approved