SNP: A Program for Nonparametric
Time Series Analysis
A. Ronald Gallant
Fuqua
Duke University
DUMC
Phone: 919-660-7927 (Duke-Fuqua)
e-mail: ron.gallant@duke.edu
George Tauchen
Department of Economics
Duke University
Durham NC 27708-0097
Phone 1-919-660-1812
FAX 1-919-684-8974
e-mail: george.tauchen@duke.edu
Keywords: nonparametric time series, nonlinear time series, hermite series
FORTRAN: Code and a User's Guide as a PostScript file are
available anonymous ftp from http://econ.duke.edu/webfiles/get/
in the folder pub/arg/snp or from the Carnegie-Mellon
University e-mail server by sending the e-mail message "send snp from general" to statlib@lib.stat.cmu.edu. The
code is provided at no charge for research purposes without warranty of any
kind, expressed or implied. The PC version is available within the ms-snp and pc-snp subdirectories
under pub/arg/snp.
C++: A recently developed C++ version with a User's Guide as a PostScript file
is available from http://econ.duke.edu/webfiles/arg
in the folder /pub/arg/snp_cpp. The same
discloser applies.
References:
Gallant, A. Ronald, and George Tauchen (1989),"Seminonparametric Estimation of Conditionally Constrained Heterogeneous Processes: Asset Pricing Applications," Econometrica 57, 1091--1120.
Gallant, A. Ronald, and George Tauchen (1992), A Nonparametric Approach to
Nonlinear Time Series Analysis: Estimation and Simulation," in David Brillinger, Peter Caines, John Geweke, Emanuel Parzen, Murray
Rosenblatt, and Murad S. Taqqu
eds. New Directions in Time Series Analysis, Part II.
Description:
SNP is a method of nonparametric time series analysis. The method employs a Hermite polynomial series expansion to approximate the conditional density of a multivariate process. An appealing feature of this expansion is that it is a nonlinear nonparametric model that directly nests the Gaussian VAR model, the semiparametric VAR model, the Gaussian GARCH model, and the multivariate BEKK GARCH. The SNP model is fitted using conventional maximum likelihood together with a model selection strategy that determines the appropriate degree of the polynomial.
Languages: FORTRAN 77 and C++
Platforms: PCs under the free GNU g77 FORTRAN and Intel FORTRAN; UNIX/LINUX workstations including SUNs, HPs, and Intel-based boxes that run either LINUX or Solaris and support cpp and f77.
Support: For more information on the SNP package contact its authors: A. Ronald Gallant, ron_gallant@unc.edu, or George Tauchen, get@econ.duke.edu.