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Non-parametric covariance estimation from irregularly-spaced data

Published online by Cambridge University Press:  01 July 2016

Elias Masry
Elias Masry*
Affiliation:
University of California at San Diego
*
∗Postal address: Department of Electrical Engineering and Computer Sciences, Mail Code C-014, University of California, San Diego, La Jolla, CA 92093, U.S.A.
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Abstract

The non-parametric discrete-time estimation of the covariance function R(t) of stationary continuous-time processes is considered. The characteristics of the sampling instants necessary for the consistent estimation of R(t) are explored. A class of covariance estimates is introduced and its asymptotic statistics are derived.

Keywords

DETERMINISTIC AND RANDOM SAMPLING SCHEMESPOISSON POINT PROCESSQUADRATIC-MEAN CONSISTENCYCONVERGENCE RATESASYMPTOTIC NORMALITY

Information

Type
Research Article
Information
Advances in Applied Probability , Volume 15 , Issue 1 , March 1983 , pp. 113 - 132
Copyright
Copyright © Applied Probability Trust 1983 

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Footnotes

This work was supported by the Office of Naval Research under Contract N000 14-75-C-0652.

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