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May, 1993 Parametric Signal Modelling using Laguerre Filters
B. Wahlberg, E. J. Hannan
Ann. Appl. Probab. 3(2): 467-496 (May, 1993). DOI: 10.1214/aoap/1177005434


Autoregressive (AR) modelling is generalized by replacing the delay operator by discrete Laguerre filters. The motivation is to reduce the number of parameters needed to obtain useful approximate models of stochastic processes, without increasing the computational complexity. Asymptotic statistical properties are investigated. Several AR model estimation results are extended to Laguerre models. In particular, it is shown how the choice of Laguerre time constant affects the resulting estimates. A Levinson-type algorithm for computing the Laguerre model estimates in an efficient way is also given. The Laguerre technique is illustrated by two simple examples.


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B. Wahlberg. E. J. Hannan. "Parametric Signal Modelling using Laguerre Filters." Ann. Appl. Probab. 3 (2) 467 - 496, May, 1993.


Published: May, 1993
First available in Project Euclid: 19 April 2007

zbMATH: 0784.62080
MathSciNet: MR1221162
Digital Object Identifier: 10.1214/aoap/1177005434

Primary: 62M10
Secondary: 60F05 , 60G10 , 60G12 , 62F12

Keywords: Autoregression , Laguerre functions , network modeling , spectral analysis , time series

Rights: Copyright © 1993 Institute of Mathematical Statistics


Vol.3 • No. 2 • May, 1993
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