Back to Search
Start Over
Gaussian process for nonstationary time series prediction
- Source :
-
Computational Statistics & Data Analysis . Nov2004, Vol. 47 Issue 4, p705-712. 8p. - Publication Year :
- 2004
-
Abstract
- In this paper, the problem of time series prediction is studied. A Bayesian procedure based on Gaussian process models using a nonstationary covariance function is proposed. Experiments proved the approach effectiveness with an excellent prediction and a good tracking. The conceptual simplicity, and good performance of Gaussian process models should make them very attractive for a wide range of problems. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 01679473
- Volume :
- 47
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Computational Statistics & Data Analysis
- Publication Type :
- Periodical
- Accession number :
- 14871680
- Full Text :
- https://doi.org/10.1016/j.csda.2004.02.006