Often the best way to adumbrate a dark and dense assemblage of material is to describe the background in contrast to which the edges of the nebulosity may be clearly discerned. Hence, perhaps the most appropriate way to introduce this paper is to describe what it is not. It is not a comprehensive study of stochastic processes, nor an in-depth treatment of convergence. In fact, on the surface, the material covered in this paper is nothing more than a compendium of seemingly loosely-connected and barely-miscible theorems, methods and conclusions from the three main papers surveyed ([VC71], [Pol89] and [DL91])
Stochastic processes are probabilistic models of data streams such as speech, audio and video signal...
The aim of the dissertation is to establish the weak convergence of mean-field interacting particle ...
The scope of this paper is to offer an overview of the main results obtained by the authors in recen...
Often the best way to adumbrate a dark and dense assemblage of material is to describe the backgroun...
Two concrete examples show us that the convergence of a family of stochastic processes "as controls"...
"This comprehensive guide to stochastic processes gives a complete overview of the theory and addres...
This extract is taken from the author's original manuscript and has not been reviewed or edited. Th...
AbstractAssuming that {(Un,Vn)} is a sequence of càdlàg processes converging in distribution to (U,V...
This work produces explicit convergence rates and properties of the stationary distributions for two...
We give a new take on the error analysis of approximations of stochastic differential equations (SDE...
The concept of the distribution function of a closed-valued measurable multifunction is introduced a...
A stochastic differential equation with vanishing martingale term is studied. Specifically, given a ...
http://www.math.washington.edu/~ejpecp/We study the limit of functionals of stochastic processes for...
A classical limit theorem of stochastic process theory concerns the sample cumulative distribution f...
Some applications of Malliavin calculus to stochastic partial differential equations (SPDEs) and to ...
Stochastic processes are probabilistic models of data streams such as speech, audio and video signal...
The aim of the dissertation is to establish the weak convergence of mean-field interacting particle ...
The scope of this paper is to offer an overview of the main results obtained by the authors in recen...
Often the best way to adumbrate a dark and dense assemblage of material is to describe the backgroun...
Two concrete examples show us that the convergence of a family of stochastic processes "as controls"...
"This comprehensive guide to stochastic processes gives a complete overview of the theory and addres...
This extract is taken from the author's original manuscript and has not been reviewed or edited. Th...
AbstractAssuming that {(Un,Vn)} is a sequence of càdlàg processes converging in distribution to (U,V...
This work produces explicit convergence rates and properties of the stationary distributions for two...
We give a new take on the error analysis of approximations of stochastic differential equations (SDE...
The concept of the distribution function of a closed-valued measurable multifunction is introduced a...
A stochastic differential equation with vanishing martingale term is studied. Specifically, given a ...
http://www.math.washington.edu/~ejpecp/We study the limit of functionals of stochastic processes for...
A classical limit theorem of stochastic process theory concerns the sample cumulative distribution f...
Some applications of Malliavin calculus to stochastic partial differential equations (SPDEs) and to ...
Stochastic processes are probabilistic models of data streams such as speech, audio and video signal...
The aim of the dissertation is to establish the weak convergence of mean-field interacting particle ...
The scope of this paper is to offer an overview of the main results obtained by the authors in recen...