Modelling of Multivariate Stationary Time Series Using Rational Approximation of the Spectral Density Function and Wavelet Coherence

Chithralekha. K^1, and Jessy John C¹

¹Department of Mathematics, National Institute of Technology Calicut, India

Cite this paper:
Chithralekha. K and Jessy John C. Modelling of Multivariate Stationary Time Series Using Rational Approximation of the Spectral Density Function and Wavelet Coherence. Journal of Mathematical Sciences and Applications. 2017; 5(1):1-16. doi: 10.12691/jmsa-5-1-1

Abstract

This paper presents a new method for the modelling of multivariate stationary time series by applying multiple input-single output transfer function noise model, rational approximation of spectral density function and wavelet coherence. Parameter estimation process is simple and the number of parameters needs to be estimated is very less, is the main advantage of this method. The method is verified by simulation studies and it is also applied to model US hog data with five component series.

Keywords:
multivariate stationary time series spectral density functions the rational approximation of spectral density functions wavelet coherence

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