A Fast Algorithm for the BDS Statistic
Blake Lebaron ()
Studies in Nonlinear Dynamics & Econometrics, 1997, vol. 2, issue 2, 1-9
The BDS statistic has proved to be one of several useful nonlinear diagnostics. It has been shown to have good power against many nonlinear alternatives, and its asymptotic properties as a residual diagnostic are well understood. Furthermore, extensive Monte Carlo results have proved it useful in relatively small samples. However, the BDS test is not trivial to calculate, and is even more difficult to deal with if one wants the speed necessary to make bootstrap resampling feasible. This short paper presents a fast algorithm for the BDS statistic, and outlines how these speed improvements are achieved. Source code in the C programming language is included.
References: Add references at CitEc
Citations: View citations in EconPapers (9) Track citations by RSS feed
Downloads: (external link)
https://www.degruyter.com/view/j/snde.1997.2.2/snd ... .1029.xml?format=INT (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:bpj:sndecm:v:2:y:1997:i:2:n:al1
Ordering information: This journal article can be ordered from
Access Statistics for this article
Studies in Nonlinear Dynamics & Econometrics is currently edited by Bruce Mizrach
More articles in Studies in Nonlinear Dynamics & Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().