Kalman filter estimation for periodic autoregressive-moving average models

C. Jimenez; A. I. McLeod; K. W. Hipel

doi:10.1007/BF01543862

Kalman filter estimation for periodic autoregressive-moving average models

C. Jimenez^*
, A. I. McLeod
, K. W. Hipel

^*Corresponding author for this work

Western University
University of Waterloo

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

Abstract

An exact maximum likelihood procedure is presented for estimating the parameters of a periodic autogressive-moving average (PARMA) model. To develop an estimator which is both statistically and computationally efficient, the PARMA class of models is written using a state-space representation and a Kalman filtering algorithm is used to estimate the parameters. In order to demonstrate how to fit PARMA models in practice, the most appropriate types of PARMA models are identified for fitting to two average monthly riverflow time series and the new estimator is employed for estimating the model parameters.

Original language	English
Pages (from-to)	227-240
Number of pages	14
Journal	Stochastic Hydrology and Hydraulics
Volume	3
Issue number	3
DOIs	https://doi.org/10.1007/BF01543862
State	Published - Sep 1989
Externally published	Yes

Keywords

Kalman filter
Maximum likelihood estimation
Periodic models
Stochastic hydrology
Time series analysis

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10.1007/BF01543862

Cite this

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title = "Kalman filter estimation for periodic autoregressive-moving average models",

abstract = "An exact maximum likelihood procedure is presented for estimating the parameters of a periodic autogressive-moving average (PARMA) model. To develop an estimator which is both statistically and computationally efficient, the PARMA class of models is written using a state-space representation and a Kalman filtering algorithm is used to estimate the parameters. In order to demonstrate how to fit PARMA models in practice, the most appropriate types of PARMA models are identified for fitting to two average monthly riverflow time series and the new estimator is employed for estimating the model parameters.",

keywords = "Kalman filter, Maximum likelihood estimation, Periodic models, Stochastic hydrology, Time series analysis",

author = "C. Jimenez and McLeod, \{A. I.\} and Hipel, \{K. W.\}",

year = "1989",

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doi = "10.1007/BF01543862",

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T1 - Kalman filter estimation for periodic autoregressive-moving average models

AU - Jimenez, C.

AU - McLeod, A. I.

AU - Hipel, K. W.

PY - 1989/9

Y1 - 1989/9

N2 - An exact maximum likelihood procedure is presented for estimating the parameters of a periodic autogressive-moving average (PARMA) model. To develop an estimator which is both statistically and computationally efficient, the PARMA class of models is written using a state-space representation and a Kalman filtering algorithm is used to estimate the parameters. In order to demonstrate how to fit PARMA models in practice, the most appropriate types of PARMA models are identified for fitting to two average monthly riverflow time series and the new estimator is employed for estimating the model parameters.

AB - An exact maximum likelihood procedure is presented for estimating the parameters of a periodic autogressive-moving average (PARMA) model. To develop an estimator which is both statistically and computationally efficient, the PARMA class of models is written using a state-space representation and a Kalman filtering algorithm is used to estimate the parameters. In order to demonstrate how to fit PARMA models in practice, the most appropriate types of PARMA models are identified for fitting to two average monthly riverflow time series and the new estimator is employed for estimating the model parameters.

KW - Kalman filter

KW - Maximum likelihood estimation

KW - Periodic models

KW - Stochastic hydrology

KW - Time series analysis

UR - https://www.scopus.com/pages/publications/0024799931

U2 - 10.1007/BF01543862

DO - 10.1007/BF01543862

M3 - Artículo

AN - SCOPUS:0024799931

SN - 0931-1955

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JO - Stochastic Hydrology and Hydraulics

JF - Stochastic Hydrology and Hydraulics

IS - 3

ER -

Kalman filter estimation for periodic autoregressive-moving average models

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Keywords

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