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

Wilfried Loges

Journal of Multivariate Analysis, 1986, vol. 20, issue 1, 161-174

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.

Date: 1986
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0047-259X(86)90026-6
Full text for ScienceDirect subscribers only

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:eee:jmvana:v:20:y:1986:i:1:p:161-174

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

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
Bibliographic data for series maintained by Catherine Liu ().