Canonical correlation in multivariate time series analysis

Zaka Ratsimalahelo
Additional contact information
Zaka Ratsimalahelo: LATEC - Laboratoire d'Analyse et de Techniques Economiques [UMR 5601] - UB - Université de Bourgogne - CNRS - Centre National de la Recherche Scientifique

Working Papers from HAL

Abstract: We analyze a class o f state space identification algorithms for time series, based on canonical correlation analysis in the ligth of recent results on stochastic systems theory calle d « subspace methods » .These can be describe as covariance estimation followed b y stochastic realization . The methods offer the major advantage o f converting the nonlinear parameter estimation phase in traditional V A R M A models identification in to the solution o f Riccati equation but introduce at the same time some no n trivial mathematical problem s related to positivity. The states o f the forward - backward innovations representation have an interpretation : Instrumental Variables estimators .

Keywords: balancing; eEconomics; economic theory; innovation model; instrumental variables estimtors; singular value decomposition; statistics; operations research; subspace methods (search for similar items in EconPapers)
Date: 1997
Note: View the original document on HAL open archive server: https://hal.science/hal-01526992v1
References: Add references at CitEc
Citations:

Published in [Research Report] Laboratoire d'analyse et de techniques économiques(LATEC). 1997, 13 p., ref. bib. : 1 p

Downloads: (external link)
https://hal.science/hal-01526992v1/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:hal-01526992

Access Statistics for this paper

More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().