METHOD OF IDENTIFICATION OF AUTOREGRESSION-SLIDING MEAN (ARSM) MODEL (Р,Q) WITH RANDOM VALUES OF Р, Q, ORDERS THAT GENERALIZES YULE–WORKER TECHNIQUE

  • Oleksandr Mokin Vinnytsia National Technical University
  • Vitaliy Mokin Vinnytsia National Technical University
  • Borys Mokin Vinnytsia National Technical University
Keywords: time series, model of autoregression-sliding mean, Yule-Worker technique, non-linear complement of Yule-Worker technique

Abstract

Method of identification of autoregression sliding mean (ARSM) (р,q) model with random values of
р,q,orders, that generalizes Yule-Worker technique, developed for identification of the model of
autoregression АР(р), in case, when autoregressive component of АР(р) model is complemented with the
component of sliding mean SM(q, is suggested). Algorithm of the suggested method contains both the system
of linear equations of Yule-Worker type for determination of р parameters of autoregression and additional
non-linear equations for identification of q parameters of sliding mean. Operation of the algorithm was
demonstrated on the example p = 3, q = 3.

 

 

 

REFERENCES
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Author Biographies

Oleksandr Mokin, Vinnytsia National Technical University

Doctor of Science (Eng), Professor, Head of the Chair of Renewable Power and
Transport Electric Systems and Complexes (RETESC)

Vitaliy Mokin, Vinnytsia National Technical University

Doctor of Science (Eng), Professor, Head of the Chair of Computer Ecological and
Economic Monitoring and Engineering Graphics (CEEMEG)

Borys Mokin, Vinnytsia National Technical University

Academician of NAPSU, Doctor of Science (Eng), Professor, Department of Renewable
Power and Transport Electric Systems and Complexes

Published
2015-11-25
How to Cite
[1]
O. Mokin, V. Mokin, and B. Mokin, “METHOD OF IDENTIFICATION OF AUTOREGRESSION-SLIDING MEAN (ARSM) MODEL (Р,Q) WITH RANDOM VALUES OF Р, Q, ORDERS THAT GENERALIZES YULE–WORKER TECHNIQUE”, SWVNTU, no. 2, Nov. 2015.
Section
Information Technologies and Computer Engineering

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