Parameter Estimation for p-Order Random Coefficient Autoregressive (RCA) Models Based on Kalman Filter

In this paper we elaborate an algorithm to estimate p-order Random Coefficient Autoregressive Model (RCA(p)) parameters. This algorithm combines quasi-maximum likelihood method, the Kalman filter, and the simulated annealing method. In the aim to generalize the results found for RCA(1), we have inte...

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Main Authors: Mohammed Benmoumen, Jelloul Allal, Imane Salhi
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2019/8479086
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author Mohammed Benmoumen
Jelloul Allal
Imane Salhi
author_facet Mohammed Benmoumen
Jelloul Allal
Imane Salhi
author_sort Mohammed Benmoumen
collection DOAJ
description In this paper we elaborate an algorithm to estimate p-order Random Coefficient Autoregressive Model (RCA(p)) parameters. This algorithm combines quasi-maximum likelihood method, the Kalman filter, and the simulated annealing method. In the aim to generalize the results found for RCA(1), we have integrated a subalgorithm which calculate the theoretical autocorrelation. Simulation results demonstrate that the algorithm is viable and promising.
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institution Kabale University
issn 1110-757X
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language English
publishDate 2019-01-01
publisher Wiley
record_format Article
series Journal of Applied Mathematics
spelling doaj-art-973141478e0d4e54b85ed596378243332025-02-03T05:47:57ZengWileyJournal of Applied Mathematics1110-757X1687-00422019-01-01201910.1155/2019/84790868479086Parameter Estimation for p-Order Random Coefficient Autoregressive (RCA) Models Based on Kalman FilterMohammed Benmoumen0Jelloul Allal1Imane Salhi2LaMSD, Faculty of Sciences, Mohammed Premier University, Oujda, MoroccoLaMSD, Faculty of Sciences, Mohammed Premier University, Oujda, MoroccoLaMSD, Faculty of Sciences, Mohammed Premier University, Oujda, MoroccoIn this paper we elaborate an algorithm to estimate p-order Random Coefficient Autoregressive Model (RCA(p)) parameters. This algorithm combines quasi-maximum likelihood method, the Kalman filter, and the simulated annealing method. In the aim to generalize the results found for RCA(1), we have integrated a subalgorithm which calculate the theoretical autocorrelation. Simulation results demonstrate that the algorithm is viable and promising.http://dx.doi.org/10.1155/2019/8479086
spellingShingle Mohammed Benmoumen
Jelloul Allal
Imane Salhi
Parameter Estimation for p-Order Random Coefficient Autoregressive (RCA) Models Based on Kalman Filter
Journal of Applied Mathematics
title Parameter Estimation for p-Order Random Coefficient Autoregressive (RCA) Models Based on Kalman Filter
title_full Parameter Estimation for p-Order Random Coefficient Autoregressive (RCA) Models Based on Kalman Filter
title_fullStr Parameter Estimation for p-Order Random Coefficient Autoregressive (RCA) Models Based on Kalman Filter
title_full_unstemmed Parameter Estimation for p-Order Random Coefficient Autoregressive (RCA) Models Based on Kalman Filter
title_short Parameter Estimation for p-Order Random Coefficient Autoregressive (RCA) Models Based on Kalman Filter
title_sort parameter estimation for p order random coefficient autoregressive rca models based on kalman filter
url http://dx.doi.org/10.1155/2019/8479086
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AT jelloulallal parameterestimationforporderrandomcoefficientautoregressivercamodelsbasedonkalmanfilter
AT imanesalhi parameterestimationforporderrandomcoefficientautoregressivercamodelsbasedonkalmanfilter