Multivariate Time Series Analysis and Forecast

György Bánkövi, József Veliczky and Margit Ziermann
Additional contact information
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

A chapter in Probability and Statistical Inference, 1982, pp 29-34 from Springer

Abstract: 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.

Keywords: National Economy; Dynamic Factor; European Economic Community; Vector Process; Artificial Variable (search for similar items in EconPapers)
Date: 1982
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-94-009-7840-9_4

Ordering information: This item can be ordered from
http://www.springer.com/9789400978409

DOI: 10.1007/978-94-009-7840-9_4

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().