Estimation of parameters for Hilbert space-valued partially observable stochastic processes

We give the asymptotic statistical theory (strong consistency and asymptotic normality) of a modified least-square-estimator for the parameters of a linear time discrete Kalman-filter-system. The method of proof uses a strong law of large numbers for martingale difference and ergodic sequences and a central limit theorem for q-dependent stationary processes.

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Year of publication:	1986
Authors:	Loges, Wilfried
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 20.1986, 1, p. 161-174
Publisher:	Elsevier

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005199821