Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
415419 | Computational Statistics & Data Analysis | 2008 | 12 Pages |
Abstract
Two new forecasting methods of time series are introduced. They are both based on a factorial analysis method called spline principal component analysis with respect to instrumental variables (spline PCAIV). The first method is a straightforward application of spline PCAIV while the second one is an adaptation of spline PCAIV. In the modified version, the used criteria according to the unknown value that need to be predicted are differentiated. Those two forecasting methods are shown to be well adapted to time series.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
P.-A. Cornillon, W. Imam, E. Matzner-Løber,