A Combinatorial Approach to Piecewise Linear Time Series Analysis

Marcelo Medeiros (), Alvaro Veiga () and Mauricio Resende ()
Additional contact information
Alvaro Veiga: Dept. of Electrical Engineering, Postal: Catholic University of Rio de Janeiro (PUC-Rio), Rua Marquês de São Vicente 225, Rio de Janeiro, RJ, Brazil, 22453-900
Mauricio Resende: Information Sciences Research Center, Algorithms and Optimization Research Department, Postal: AT&T Labs Research, Room C241, 180 Park Avenue, P. O. Box 971, Florham Park, NJ 07932-0971, USA

No 393, SSE/EFI Working Paper Series in Economics and Finance from Stockholm School of Economics

Abstract: Over recent years, several nonlinear time series models have been proposed in the literature. One model that has found a large number of successful applications is the threshold autoregressive model (TAR). The TAR model is a piecewise linear process whose central idea is to change the parameters of a linear autoregressive model according to the value of an observable variable, called the threshold variable. If this variable is a lagged value of the time series, the model is called a self-exciting threshold autoregressive (SETAR) model. In this paper, we propose a heuristic to estimate a more general SETAR model, where the thresholds are multivariate. We formulated the task of finding multivariate thresholds as a combinatorial optimization problem. We developed an algorithm based on a Greedy Randomized Adaptive Search Procedure (GRASP) to solve the problem. GRASP is an iterative randomized sampling technique that has been shown to quickly produce good quality solutions for a wide variety of optimization problems. The proposed model performs well on both simulated and real data.

Keywords: nonlinear time series; piecewise linear models; combinatorial optimization; search heuristic; GRASP (search for similar items in EconPapers)
JEL-codes: C22 C51 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2000-06-26
New Economics Papers: this item is included in nep-ecm and nep-ets
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Published in Journal of Computational and Graphical Statistics, 2002, pages 236-258.

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:hhs:hastef:0393

Access Statistics for this paper

More papers in SSE/EFI Working Paper Series in Economics and Finance from Stockholm School of Economics The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, 113 83 Stockholm, Sweden. Contact information at EDIRC.
Bibliographic data for series maintained by Helena Lundin ().