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Wavelets in state space models
Author(s) -
Zandonade Eliana,
Morettin Pedro A.
Publication year - 2003
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.496
Subject(s) - kalman filter , wavelet , series (stratigraphy) , state space , state space representation , computer science , algorithm , state (computer science) , space (punctuation) , extended kalman filter , artificial intelligence , econometrics , mathematics , statistics , geology , paleontology , operating system
In this paper, we consider the utilization of wavelets in conjunction with state space models. Specifically, the parameters in the system matrix are expanded in wavelet series and estimated via the Kalman Filter and the EM algorithm. In particular this approach is used for switching models. Two applications are given, one to the problem of detecting the paths of targets using an array of sensors, and the other to a series of daily spreads between two Brazilian bonds. Copyright © 2003 John Wiley & Sons, Ltd.