This is the published version, also available here: http://dx.doi.org/10.1214/aop/1176988183.The purpose of this paper is to prove a characterization of the conditional independence of two independent random variables given a particular functional of them, in terms of a factorization property. As an application we discuss the Markov field property for solutions of stochastic differential equations with a boundary condition involving the values of the process at times t=0 and t=1
Goldys B, Röckner M, Zhang X. Martingale solutions and Markov selections for stochastic partial diff...
The goal of the paper is to recall a recently introduced concept of conditional independence in evid...
Abstract—We take the point of view that a Markov random field is a collection of so-called full cond...
The purpose of this paper is to prove a characterization of the conditional independence of two inde...
In this paper we first present a multidimensional version of the characterization of the conditional...
This is the publisher's version, also available electronically from http://www.jstor.org/stable/3318...
This paper deals with the relationship between two-dimensional parameter Gaussian random fields veri...
This is the published version, also available here: http://dx.doi.org/10.1214/aop/1176990337.In this...
We consider linear nth order stochastic differential equations on [0, 1], with linear boundary condi...
In the present paper we study the one-dimensional stochastic difference equation Xn+1 = Xn + f(Xn) +...
The martingale problem associated to the three-dimensional Navier–Stokes equations is shown to have ...
AbstractIn the present paper we study the one-dimensional stochastic difference equation Xn+1 = Xn +...
In the present paper we study the one-dimensional stochastic difference equation x(n + 1) = X(n) + f...
In this paper we show that the solution of a second-order stochastic differential equation with diff...
The aim of this work is to describe the conditional law of a multidimensional Markov process knowing...
Goldys B, Röckner M, Zhang X. Martingale solutions and Markov selections for stochastic partial diff...
The goal of the paper is to recall a recently introduced concept of conditional independence in evid...
Abstract—We take the point of view that a Markov random field is a collection of so-called full cond...
The purpose of this paper is to prove a characterization of the conditional independence of two inde...
In this paper we first present a multidimensional version of the characterization of the conditional...
This is the publisher's version, also available electronically from http://www.jstor.org/stable/3318...
This paper deals with the relationship between two-dimensional parameter Gaussian random fields veri...
This is the published version, also available here: http://dx.doi.org/10.1214/aop/1176990337.In this...
We consider linear nth order stochastic differential equations on [0, 1], with linear boundary condi...
In the present paper we study the one-dimensional stochastic difference equation Xn+1 = Xn + f(Xn) +...
The martingale problem associated to the three-dimensional Navier–Stokes equations is shown to have ...
AbstractIn the present paper we study the one-dimensional stochastic difference equation Xn+1 = Xn +...
In the present paper we study the one-dimensional stochastic difference equation x(n + 1) = X(n) + f...
In this paper we show that the solution of a second-order stochastic differential equation with diff...
The aim of this work is to describe the conditional law of a multidimensional Markov process knowing...
Goldys B, Röckner M, Zhang X. Martingale solutions and Markov selections for stochastic partial diff...
The goal of the paper is to recall a recently introduced concept of conditional independence in evid...
Abstract—We take the point of view that a Markov random field is a collection of so-called full cond...