On multivariate fractional random fields: tempering and operator-stable laws

TL;DR

This paper introduces a new class of multivariate random fields called tempered operator fractional operator-stable fields, generalizing existing models with broad applications in stochastic processes.

Contribution

It defines and analyzes the properties of TRF, a broad family of non-Gaussian, operator-stable random fields, including their subclasses and path properties.

Findings

Established existence and fundamental properties of TRF.

Proved equivalence of subclasses under Gaussianity and isotropy.

Analyzed sample path properties for Gaussian instances.

Abstract

In this paper, we define a new and broad family of vector-valued random fields called tempered operator fractional operator-stable random fields (TRF, for short). TRF is typically non-Gaussian and generalizes tempered fractional stable stochastic processes. TRF comprises moving average and harmonizable-type subclasses that are constructed by tempering (matrix-) homogeneous, matrix-valued kernels in time- and Fourier-domain stochastic integrals with respect to vector-valued, strictly operator-stable random measures. We establish the existence and fundamental properties of TRF. Assuming both Gaussianity and isotropy, we show the equivalence between certain moving average and harmonizable subclasses of TRF. In addition, we establish sample path properties in the scalar-valued case for several Gaussian instances.