 Generalized canonical analysis for time seriesP. M. Robinson Journal of Multivariate Analysis, 1973, vol. 3, issue 2, 141-160 Abstract: Canonical correlation analysis is shown to be equivalent to the problem of estimating a linear regression matrix, B0, of less than full rank. After reparameterizing B0 some estimates of the new parameters, obtained by solving an eigenvalue problem and closely related to canonical correlations and vectors, are found to be consistent and efficient when the residuals are mutually independent. When the residuals are generated by an autocorrelated, stationary time series these estimates are still consistent and obey a central limit theorem, but they are no longer efficient. Alternative, more general estimates are suggested which are efficient in the presence of serial correlation. Asymptotic theory and iterative computational procedures for these estimates are given. A likelihoodratio test for the rank of B0 is seen to be an extension of a familiar test for canonical correlations. Keywords: Canonical; correlation; serially; correlated; residuals; Fourier; methods; asymptotic; theory; stationary; time; series (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:3:y:1973:i:2:p:141-160 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of Multivariate Analysis is currently edited by de Leeuw, J. More articles in Journal of Multivariate Analysis from Elsevier |
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