Padé approximation and its application in time series analysis

Kuldeep Kumar

doi:10.1016/0096-3003(92)90034-X

Padé approximation and its application in time series analysis

Kuldeep Kumar^*

^*Corresponding author for this work

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

Abstract

Since the appearance in 1970 of the book by Box and Jenkins, the use of the auto regressive-moving average (ARMA) model has become widespread in many fields for the analysis and prediction of time series data. However, one of the main criticisms of these ARMA models is that they are difficult to specify. In this paper we have proposed a new method based on the theory of Padé approximations for the estimation of parameters and specification of the order of ARMA (p,q) models. Simulation results and results obtained from applying this method to real data sets substantiate our claim for using this method.

Original language	English
Pages (from-to)	139-151
Number of pages	12
Journal	Applied Mathematics and Computation
Volume	48
Issue number	2-3
DOIs	https://doi.org/10.1016/0096-3003(92)90034-X
Publication status	Published - 1992
Externally published	Yes

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10.1016/0096-3003(92)90034-X

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title = "Pad{\'e} approximation and its application in time series analysis",

abstract = "Since the appearance in 1970 of the book by Box and Jenkins, the use of the auto regressive-moving average (ARMA) model has become widespread in many fields for the analysis and prediction of time series data. However, one of the main criticisms of these ARMA models is that they are difficult to specify. In this paper we have proposed a new method based on the theory of Pad{\'e} approximations for the estimation of parameters and specification of the order of ARMA (p,q) models. Simulation results and results obtained from applying this method to real data sets substantiate our claim for using this method.",

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AB - Since the appearance in 1970 of the book by Box and Jenkins, the use of the auto regressive-moving average (ARMA) model has become widespread in many fields for the analysis and prediction of time series data. However, one of the main criticisms of these ARMA models is that they are difficult to specify. In this paper we have proposed a new method based on the theory of Padé approximations for the estimation of parameters and specification of the order of ARMA (p,q) models. Simulation results and results obtained from applying this method to real data sets substantiate our claim for using this method.

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JO - Applied Mathematics and Computation

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Padé approximation and its application in time series analysis

Abstract

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