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Multivariate Time Series Analysis and Forecast

In: Probability and Statistical Inference

Author

Listed:
  • György Bánkövi

    (Computer Centre of the National Planning Office)

  • József Veliczky

    (Computer Centre of the National Planning Office)

  • Margit Ziermann

    (Institute of Economic Planning of the National Planning Office)

Abstract

It is well known that the multivariate computer-oriented methods of mathematical statistics are based on independent vector variables essentially. This is why the authors have been concerned, for a decade already, in the elaboration of procedures which could be considered as ”dynamized” variants of the principal component analysis or, in general, the factor analysis. Recently the authors succeeded in the extension of their approaches, called dynamic factor analysis, to matrix processes estimated in some constant interval (mostly at yearly). This procedure, which seems to be subject of special interest in case of applications in economics, will be presented in the paper.

Suggested Citation

  • György Bánkövi & József Veliczky & Margit Ziermann, 1982. "Multivariate Time Series Analysis and Forecast," Springer Books, in: Wilfried Grossmann & Georg Ch. Pflug & Wolfgang Wertz (ed.), Probability and Statistical Inference, pages 29-34, Springer.
    • Handle: RePEc:spr:sprchp:978-94-009-7840-9_4
    DOI: 10.1007/978-94-009-7840-9_4
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