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arXiv · 1609.03470

Joint Asymptotics for Estimating the Fractal Indices of Bivariate Gaussian Processes

Yuzhen Zhou·Yimin Xiao
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Abstract

Multivariate (or vector-valued) processes are important for modeling multiple variables. The fractal indices of the components of the underlying multivariate process play a key role in characterizing the dependence structures and statistical properties of the multivariate process. In this paper, under the infill asymptotics framework, we establish joint asymptotic results for the increment-based estimators of bivariate fractal indices. Our main results quantitatively describe the effect of the cross-dependence structure on the performance of the estimators.

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Yuzhen Zhou, Yimin Xiao. 2016-09-12. Joint Asymptotics for Estimating the Fractal Indices of Bivariate Gaussian Processes. https://arxiv.org/abs/1609.03470

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