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

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  • Loges, Wilfried

Abstract

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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  • Loges, Wilfried, 1986. "Estimation of parameters for Hilbert space-valued partially observable stochastic processes," Journal of Multivariate Analysis, Elsevier, vol. 20(1), pages 161-174, October.
    • Handle: RePEc:eee:jmvana:v:20:y:1986:i:1:p:161-174
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    Cited by:

    1. Kara-Terki, Nesrine & Mourid, Tahar, 2016. "On local asymptotic normality for functional autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 148(C), pages 120-140.

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