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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2019-01-01
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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. |
format | Article |
id | doaj-art-973141478e0d4e54b85ed59637824333 |
institution | Kabale University |
issn | 1110-757X 1687-0042 |
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 |
work_keys_str_mv | AT mohammedbenmoumen parameterestimationforporderrandomcoefficientautoregressivercamodelsbasedonkalmanfilter AT jelloulallal parameterestimationforporderrandomcoefficientautoregressivercamodelsbasedonkalmanfilter AT imanesalhi parameterestimationforporderrandomcoefficientautoregressivercamodelsbasedonkalmanfilter |