The concepts of canonical correlations and canonical components are familiar ideas in multivariate statistics. In this paper we extend these notions to stationary time series with a view to determining the most predictable aspect of the future of a time series. We relate properties of the canonical description of a time series to well known structural properties of the series such as (i) rational spectra (i.e., ARMA series), (ii) strong mixing, (iii) absolute regularity, etc.
Publié le : 1983-09-14
Classification:
Time series,
spectrum,
prediction theory,
canonical correlations,
strong mixing,
62M15,
60G25,
47B35
@article{1176346250,
author = {Jewell, Nicholas P. and Bloomfield, Peter},
title = {Canonical Correlations of Past and Future for Time Series: Definitions and Theory},
journal = {Ann. Statist.},
volume = {11},
number = {1},
year = {1983},
pages = { 837-847},
language = {en},
url = {http://dml.mathdoc.fr/item/1176346250}
}
Jewell, Nicholas P.; Bloomfield, Peter. Canonical Correlations of Past and Future for Time Series: Definitions and Theory. Ann. Statist., Tome 11 (1983) no. 1, pp. 837-847. http://gdmltest.u-ga.fr/item/1176346250/