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Feedback Linear Estimation of ARMA Processes

IFAC Proceedings Volumes, 1985
Abstract A four-step algorithm of FLE (Feedback Linear Estimation) based on the feedback control principle for ARMA processes is presented in this paper. The proposed algorithm uses three linear least square estimators and a linear filter. Linear estimations are utilized as a tool throughout the algorithm. The physical meaning of FLE is discussed and
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Innovation algorithm in ARMA process

Korean Journal of Computational & Applied Mathematics, 1998
Summary: Most of the works in Time Series Analysis are based on the Auto Regressive Integrated Moving Average (ARIMA) Box and Jenkins models. If the data exhibits no apparent deviation from stationarity and if it has rapidly decreasing autocorrelation function then a suitable ARMA\((p,q)\) model is fit to the given data. Selection of the orders of \(p\)
Sreenivasan, M., Sumathi, K.
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The Estimation of ARMA Processes

1984
A description is given of a method for estimating an ARMA process, y(t) , from observations for t=1, 2, ...T, and following this a discussion is given of the theory necessary for the validation of the method. The first stage of the method involves the fitting of an autoregression, of order hT determined by a criterion such as AIC. The asymptotic theory
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ARMA Systems andĀ ARMA Processes

2022
Manfred Deistler, Wolfgang Scherrer
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Univariate ARMA Processes

2017
If q = 0, then X t is also called an autoregressive process of order p, or AR(p) process. If p = 0, then X t is also called a moving average process of order p, or MA(q) process.
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On transformations of multivariate ARMA processes

Kybernetika, 1988
Summary: Transformations of multivariate ARMA processes are investigated such that they preserve the ARMA structure. A theorem is given that characterizes a multivariate ARMA process using a property of its covariance function. The theorem is applied to the linear transformation of a multivariate ARMA process and to the scalar product of two ARMA ...
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On the Calibration of ARMA Processes for Simulation

1987
Auto-Regressive Moving-Average processes have found increased application in recent years in connection with simulation of stochastic loads on structures. Computational efficiency and limitations on available time for simulation in connection with tests require the number of coefficients in the ARMA process to be small, thereby stressing the need for ...
S. Krenk, J. Clausen
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Linear estimation of ARMA processes

Automatica, 1983
E. J. Hannan, L. Kavalieris
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Linear identification of ARMA processes

Automatica, 1982
David Q. Mayne, F. Firoozan
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Investigations into Seasonal ARMA processes

2022
This thesis examines issues of seasonality in ARMA processes, comparing and contrasting Box-Jenkins seasonality with Gegenbauer seasonality, and the SGAR or seasonal GAR model. Novel contributions of this thesis include new estimation methods for Gegenbauer seasonality - a log-Whittle estimator and a Bayesian MCMC estimator using a Whittle likelihood ...
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