Padé approximation and its application in time series analysis

Research output: Contribution to journalArticleResearchpeer-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 languageEnglish
Pages (from-to)139-151
Number of pages12
JournalApplied Mathematics and Computation
Volume48
Issue number2-3
DOIs
Publication statusPublished - 1992
Externally publishedYes

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Time series analysis
Time Series Analysis
Autoregressive Moving Average Model
Approximation
Autoregressive Moving Average
Time Series Data
Time series
Specification
Specifications
Prediction
Simulation
Model

Cite this

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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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Padé approximation and its application in time series analysis. / Kumar, Kuldeep.

In: Applied Mathematics and Computation, Vol. 48, No. 2-3, 1992, p. 139-151.

Research output: Contribution to journalArticleResearchpeer-review

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