Multivariate random fields whose distributions are invariant under operator-scalings in both the time domain and the state space are studied. Such random fields are called operator-self-similar random fields and their scaling operators are characterized. Two classes of operator-self-similar stable random fields with values in are constructed by utilizing homogeneous functions and stochastic integral representations.Random fields Operator-self-similarity Anisotropy Gaussian random fields Stable random fields Stochastic integral representation
AbstractIn this work, a general representation for an operator self-similar Gaussian vector field is...
Operator fractional Brownian fields (OFBFs) are Gaussian, stationary-increment vector random fields ...
29 pagesInternational audienceThis article introduces the operator-scaling random ball model, genera...
AbstractMultivariate random fields whose distributions are invariant under operator-scalings in both...
We propose an explicit way to generate a class of Operator scaling stable random Gaussian fields (OS...
AbstractA scalar valued random field {X(x)}x∈Rd is called operator-scaling if for some d×d matrix E ...
International audienceIn this paper, we define and study a new class of random fields called harmoni...
A scalar valued random field {X (x)}x∈Rd is called operator-scaling if for some d × d matrix E with ...
AbstractWe investigate the sample path regularity of operator scaling α-stable random fields. Such f...
International audienceWe investigate the sample paths regularity of operator scaling alpha-stable ra...
We study the sample paths properties of Operator scaling Gaussian random fields. Such fields are ani...
International audienceWe propose an explicit way to generate a large class of Operator scaling Gauss...
In this paper we defi ne a special class of group self-similar Gaussian fields. We present an harmon...
Abstract. We study generalized random fields which arise as rescaling limits of spa-tial configurati...
AbstractWe establish several methods for constructing stationary self-similar random fields (ssf's) ...
AbstractIn this work, a general representation for an operator self-similar Gaussian vector field is...
Operator fractional Brownian fields (OFBFs) are Gaussian, stationary-increment vector random fields ...
29 pagesInternational audienceThis article introduces the operator-scaling random ball model, genera...
AbstractMultivariate random fields whose distributions are invariant under operator-scalings in both...
We propose an explicit way to generate a class of Operator scaling stable random Gaussian fields (OS...
AbstractA scalar valued random field {X(x)}x∈Rd is called operator-scaling if for some d×d matrix E ...
International audienceIn this paper, we define and study a new class of random fields called harmoni...
A scalar valued random field {X (x)}x∈Rd is called operator-scaling if for some d × d matrix E with ...
AbstractWe investigate the sample path regularity of operator scaling α-stable random fields. Such f...
International audienceWe investigate the sample paths regularity of operator scaling alpha-stable ra...
We study the sample paths properties of Operator scaling Gaussian random fields. Such fields are ani...
International audienceWe propose an explicit way to generate a large class of Operator scaling Gauss...
In this paper we defi ne a special class of group self-similar Gaussian fields. We present an harmon...
Abstract. We study generalized random fields which arise as rescaling limits of spa-tial configurati...
AbstractWe establish several methods for constructing stationary self-similar random fields (ssf's) ...
AbstractIn this work, a general representation for an operator self-similar Gaussian vector field is...
Operator fractional Brownian fields (OFBFs) are Gaussian, stationary-increment vector random fields ...
29 pagesInternational audienceThis article introduces the operator-scaling random ball model, genera...