Parameter estimation for operator scaling random fields

Operator scaling random fields are useful for modeling physical phenomena with different scaling properties in each coordinate. This paper develops a general parameter estimation method for such fields which allows an arbitrary set of scaling axes. The method is based on a new approach to nonlinear regression with errors whose mean is not zero.

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Year of publication:	2014
Authors:	Lim, C.Y. ; Meerschaert, M.M. ; Scheffler, H.-P.
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 123.2014, C, p. 172-183
Publisher:	Elsevier
Subject:	Random field \| Self-similar \| Operator scaling \| Hurst index

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

Persistent link: https://www.econbiz.de/10010718987