Applications of the periodogram method for perturbed block toeplitz satrices in statistical signal processing

In this paper, we combine the periodogram method for perturbed block Toeplitz matrices with the Cholesky decomposition to give a parameter estimation method for any perturbed vector autoregressive (VAR) or vector moving average (VMA) process, when we only know a perturbed version of the sequence of...

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Detalhes bibliográficos
Autores: Gutiérrez-Gutiérrez, J. (Jesús)|||/items/c66a6378-3f3e-46d7-a0f2-019fd93a086f, Insausti-Sarasola, X. (Xabier)|||/items/c73c592e-62ec-4953-8589-5da99ac84ad7, Zárraga-Rodríguez, M. (Marta de)|||/items/d20f8020-3353-4b8b-865d-6007163d7c23
Formato: artículo
Fecha de publicación:2020
País:España
Recursos:Universidad de Navarra
Repositorio:Dadun. Depósito Académico Digital de la Universidad de Navarra
Idioma:inglés
OAI Identifier:oai:dadun.unav.edu:10171/65220
Acesso em linha:https://hdl.handle.net/10171/65220
Access Level:acceso abierto
Palavra-chave:Parameter estimation
Periodogram method for perturbed block Toeplitz matrices
The Cholesky decomposition
Vector autoregressive (VAR) processes
Vector moving average (VMA) processes
Descrição
Resumo:In this paper, we combine the periodogram method for perturbed block Toeplitz matrices with the Cholesky decomposition to give a parameter estimation method for any perturbed vector autoregressive (VAR) or vector moving average (VMA) process, when we only know a perturbed version of the sequence of correlation matrices of the process. In order to combine the periodogram method for perturbed block Toeplitz matrices with the Cholesky decomposition, we first need to generalize a known result on the Cholesky decomposition of Toeplitz matrices to perturbed block Toeplitz matrices.

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