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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Bibliographic Details
Published in:Journal of applied mathematics 2019, Vol.2019 (2019), p.1-5
Main Authors: Benmoumen, Mohammed, Salhi, Imane, Allal, Jelloul
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Autoregressive models
Computer simulation
Kalman filters
Maximum likelihood method
Order parameters
Parameter estimation
Simulated annealing
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Summary: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.
ISSN:1110-757X
1687-0042
DOI:10.1155/2019/8479086