AbstractMultivariate 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 X={X(t),t∈Rd} with values in Rm are constructed by utilizing homogeneous functions and stochastic integral representations
AbstractA stochastic process on a finite-dimensional real vector space is operator-self-similar if a...
Operator fractional Brownian fields (OFBFs) are Gaussian, stationary-increment vector random fields ...
AbstractJeanblanc et al. (Stochastic Process. Appl. 100 (2002) 223) give a representation of self-si...
AbstractMultivariate random fields whose distributions are invariant under operator-scalings in both...
Multivariate random fields whose distributions are invariant under operator-scalings in both the tim...
AbstractIn this work, a general representation for an operator self-similar Gaussian vector field is...
International audienceIn this paper, we define and study a new class of random fields called harmoni...
AbstractWe investigate the sample path regularity of operator scaling α-stable random fields. Such f...
27 pagesInternational audienceA scalar valued random field is called operator-scaling if it satisfie...
International audienceWe investigate the sample paths regularity of operator scaling alpha-stable ra...
International audienceOperator scaling Gaussian random fields, as anisotropic generalizations of sel...
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 ...
A scalar valued random field {X (x)}x∈Rd is called operator-scaling if for some d × d matrix E with ...
International audienceWe study generalized random fields which arise as rescaling limits of spatial ...
AbstractA stochastic process on a finite-dimensional real vector space is operator-self-similar if a...
Operator fractional Brownian fields (OFBFs) are Gaussian, stationary-increment vector random fields ...
AbstractJeanblanc et al. (Stochastic Process. Appl. 100 (2002) 223) give a representation of self-si...
AbstractMultivariate random fields whose distributions are invariant under operator-scalings in both...
Multivariate random fields whose distributions are invariant under operator-scalings in both the tim...
AbstractIn this work, a general representation for an operator self-similar Gaussian vector field is...
International audienceIn this paper, we define and study a new class of random fields called harmoni...
AbstractWe investigate the sample path regularity of operator scaling α-stable random fields. Such f...
27 pagesInternational audienceA scalar valued random field is called operator-scaling if it satisfie...
International audienceWe investigate the sample paths regularity of operator scaling alpha-stable ra...
International audienceOperator scaling Gaussian random fields, as anisotropic generalizations of sel...
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 ...
A scalar valued random field {X (x)}x∈Rd is called operator-scaling if for some d × d matrix E with ...
International audienceWe study generalized random fields which arise as rescaling limits of spatial ...
AbstractA stochastic process on a finite-dimensional real vector space is operator-self-similar if a...
Operator fractional Brownian fields (OFBFs) are Gaussian, stationary-increment vector random fields ...
AbstractJeanblanc et al. (Stochastic Process. Appl. 100 (2002) 223) give a representation of self-si...
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