Add to ORKGAbstract. Self-similar processes are useful models for natural systems that exhibit scaling. Operator scaling allows a different scale factor in each coordinate. This paper develops practical methods for modeling and simulation. A simulation method is devel-oped for operator scaling Lévy processes, based on a series representation, along with a Gaussian approximation of the small jumps. Several examples are given to illustrate the range of practical applications. A complete characterization of symmetries is given in two dimensions, for any exponent and spectral measure, to inform the choice of these model parameters. The paper concludes with some extensions to general operator self-similar processes. 1
We show that the intermittent dynamics observed in the inertial interval of Sabra shell model of tur...
Introduction A stochastic process Y (t) is defined as self-similar with self-similarity parameter H...
We introduce a scattering covariance matrix which provides non-Gaussian models of time-series having...
Self-similar processes are useful models for natural systems that exhibit scaling. Operator scaling ...
AbstractSelf-similar processes are useful models for natural systems that exhibit scaling. Operator ...
AbstractA stochastic process on a finite-dimensional real vector space is operator-self-similar if a...
Abstract. We consider simulation of Subϕ(Ω)-processes that are weakly self-similar with stationary i...
In the last years fractal models have become the focus of many contributions dealing with market dyn...
Operator self-similar (OSS) stochastic processes on arbitrary Banach spaces are consid-ered. If the ...
AbstractIn this work, a general representation for an operator self-similar Gaussian vector field is...
AbstractA self-similar process Z(t) has stationary increments and is invariant in law under the tran...
Abstract. We consider simulation of Sub ’ð Þ-processes that are weakly selfsimilar with stationary i...
This dissertation presents novel models for purely discrete-time self-similar processes and scale- i...
Statistical self-similarity of random processes in continuous-domains is defined through invariance ...
International audienceThis book is organized around the notions of scaling phenomena and scale invar...
We show that the intermittent dynamics observed in the inertial interval of Sabra shell model of tur...
Introduction A stochastic process Y (t) is defined as self-similar with self-similarity parameter H...
We introduce a scattering covariance matrix which provides non-Gaussian models of time-series having...
Self-similar processes are useful models for natural systems that exhibit scaling. Operator scaling ...
AbstractSelf-similar processes are useful models for natural systems that exhibit scaling. Operator ...
AbstractA stochastic process on a finite-dimensional real vector space is operator-self-similar if a...
Abstract. We consider simulation of Subϕ(Ω)-processes that are weakly self-similar with stationary i...
In the last years fractal models have become the focus of many contributions dealing with market dyn...
Operator self-similar (OSS) stochastic processes on arbitrary Banach spaces are consid-ered. If the ...
AbstractIn this work, a general representation for an operator self-similar Gaussian vector field is...
AbstractA self-similar process Z(t) has stationary increments and is invariant in law under the tran...
Abstract. We consider simulation of Sub ’ð Þ-processes that are weakly selfsimilar with stationary i...
This dissertation presents novel models for purely discrete-time self-similar processes and scale- i...
Statistical self-similarity of random processes in continuous-domains is defined through invariance ...
International audienceThis book is organized around the notions of scaling phenomena and scale invar...
We show that the intermittent dynamics observed in the inertial interval of Sabra shell model of tur...
Introduction A stochastic process Y (t) is defined as self-similar with self-similarity parameter H...
We introduce a scattering covariance matrix which provides non-Gaussian models of time-series having...