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Theory of Probability and Mathematical Statistics

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A Baxter type estimator of an unknown parameter of the covariance function in the non-Gaussian case


Author: O. O. Synyavs’ka
Translated by: N. Semenov
Original publication: Teoriya Imovirnostei ta Matematichna Statistika, tom 88 (2013).
Journal: Theor. Probability and Math. Statist. 88 (2014), 191-201
MSC (2010): Primary 42C40; Secondary 60G12
DOI: https://doi.org/10.1090/S0094-9000-2014-00927-8
Published electronically: July 24, 2014
MathSciNet review: 3112644
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Abstract: The problem of estimation of a parameter of the covariance function is studied for a non-Gaussian stochastic process. Non-asymptotic confidence intervals for the estimator are constructed by using the Baxter statistics.


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Additional Information

O. O. Synyavs’ka
Affiliation: Department of Probability Theory, Statistics, and Actuarial Mathematics, Faculty for Mechanics and Mathematics, National Taras Shevchenko University, Volodymyrs’ka Street, 64, Kyiv 01601, Ukraine
Email: olja{\textunderscore}sunjavska@ua.fm

DOI: https://doi.org/10.1090/S0094-9000-2014-00927-8
Keywords: Baxter sums, confidence interval, stochastic processes with increments belonging to the class $K$
Received by editor(s): November 7, 2012
Published electronically: July 24, 2014
Article copyright: © Copyright 2014 American Mathematical Society