Implementing Modifed Burg Algorithms in Multivariate Subset Autoregressive Modeling

A. Alexandre Trindade

Journal of Statistical Software, 2003, vol. 008, issue i05

Abstract: The large number of parameters in subset vector autoregressive models often leads one to procure fast, simple, and efficient alternatives or precursors to maximum likelihood estimation. We present the solution of the multivariate subset Yule-Walker equations as one such alternative. In recent work, Brockwell, Dahlhaus, and Trindade (2002), show that the Yule-Walker estimators can actually be obtained as a special case of a general recursive Burg-type algorithm. We illustrate the structure of this Algorithm, and discuss its implementation in a high-level programming language. Applications of the Algorithm in univariate and bivariate modeling are showcased in examples. Univariate and bivariate versions of the Algorithm written in Fortran 90 are included in the appendix, and their use illustrated.

Date: 2003-02-03
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v008i05/pap1r2.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... /v008i05/bdt.f90.zip
https://www.jstatsoft.org/index.php/jss/article/do ... v008i05/bdt2.f90.zip

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:jss:jstsof:v:008:i05

DOI: 10.18637/jss.v008.i05

Access Statistics for this article

Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis

More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().