Integral representations and properties of operator fractional Brownian motions
arXiv:1102.1822 · doi:10.3150/10-BEJ259
Abstract
Operator fractional Brownian motions (OFBMs) are (i) Gaussian, (ii) operator self-similar and (iii) stationary increment processes. They are the natural multivariate generalizations of the well-studied fractional Brownian motions. Because of the possible lack of time-reversibility, the defining properties (i)--(iii) do not, in general, characterize the covariance structure of OFBMs. To circumvent this problem, the class of OFBMs is characterized here by means of their integral representations in the spectral and time domains. For the spectral domain representations, this involves showing how the operator self-similarity shapes the spectral density in the general representation of stationary increment processes. The time domain representations are derived by using primary matrix functions and taking the Fourier transforms of the deterministic spectral domain kernels. Necessary and sufficient conditions for OFBMs to be time-reversible are established in terms of their spectral and time domain representations. It is also shown that the spectral density of the stationary increments of an OFBM has a rigid structure, here called the dichotomy principle. The notion of operator Brownian motions is also explored.
Published in at http://dx.doi.org/10.3150/10-BEJ259 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)
Cited by in corpus (8)
- Multivariate Operator-Self-Similar Random Fields
- Operator self-similar processes and functional central limit theorems
- Non-Linear Wavelet Regression and Branch & Bound Optimization for the Full Identification of Bivariate Operator Fractional Brownian Motion
- Extremes of Vector-Valued Gaussian Processes
- Tangent fields, intrinsic stationarity, and self-similarity (with a supplement on Matheron Theory)
- Wavelet eigenvalue regression for -variate operator fractional Brownian motion
- Two-dimensional fractional Brownian motion: Analysis in time and frequency domains
- Statistical Challenges in Microrheology