Connectionist Projection Pursuit Regression

William Verkooijen and Hennie Daniels

Computational Economics, 1994, vol. 7, issue 3, 155-61

Abstract: We present a novel regression method that combines projection pursuit regression with feed forward neural networks. The algorithm is presented and compared to standard neural network learning. Connectionist projection pursuit regression (CPPR) is applied to modelling the U.S. average dollar-Deutsch mark exchange rate movement using several economic indicators. The performance of CPPR is compared with the performances of other approaches to this problem. Citation Copyright 1994 by Kluwer Academic Publishers.

Date: 1994
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:kap:compec:v:7:y:1994:i:3:p:155-61

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().