AbstractTo every symmetric Markov process there correspond two random fields over the state space: a Gaussian (“free”) field φx and the occupation field Tx which describes the amount of time spent by a particle at each state. For the Brownian motion in d ⩾ 2 dimensions both fields are generalized. Using a relation between Tx and the field ξx = :φx2:/2 established in a previous publication, polynomials of the fields T and ξ are investigated. In particular, polynomials of T characterize self-intersections of the process
For a stationary random field $(X_j)_{j\in\Z^d}$ and some measure m on $\R^d$, we consider the set-i...
For a stationary random field $(X_j)_{j\in\Z^d}$ and some measure m on $\R^d$, we consider the set-i...
AbstractOur primary aim is to “build” versions of generalised Gaussian processes from simple, elemen...
AbstractTo every symmetric Markov process there correspond two random fields over the state space: a...
AbstractTo every Markov process with a symmetric transition density, there correspond two random fie...
AbstractLet Xt be the Brownian motion in Rd. The random set Γ = {(t1,…, tn, z): Xtl = ··· = Xtn = z}...
AbstractFor a d-dimensional random field X(t) define the occupation measure corresponding to the lev...
AbstractOur primary aim is to “build” versions of generalised Gaussian processes from simple, elemen...
AbstractWe consider Dynkin's polynomials of the occupation field ⋮Tn⋮ for a 2-dimensional Brownian m...
AbstractLet p(t, x, y) be a symmetric transition density with respect to a σ-finite measure m on (E,...
AbstractIn a recent paper Brydges, Fröhlich, and Spencer have successfully applied Markov chains to ...
For a stationary random field $(X_j)_{j\in\Z^d}$ and some measure m on $\R^d$, we consider the set-i...
summary:We prove a polynomial growth estimate for random fields satisfying the Kolmogorov continuity...
summary:We prove a polynomial growth estimate for random fields satisfying the Kolmogorov continuity...
For a stationary random field $(X_j)_{j\in\Z^d}$ and some measure m on $\R^d$, we consider the set-i...
For a stationary random field $(X_j)_{j\in\Z^d}$ and some measure m on $\R^d$, we consider the set-i...
For a stationary random field $(X_j)_{j\in\Z^d}$ and some measure m on $\R^d$, we consider the set-i...
AbstractOur primary aim is to “build” versions of generalised Gaussian processes from simple, elemen...
AbstractTo every symmetric Markov process there correspond two random fields over the state space: a...
AbstractTo every Markov process with a symmetric transition density, there correspond two random fie...
AbstractLet Xt be the Brownian motion in Rd. The random set Γ = {(t1,…, tn, z): Xtl = ··· = Xtn = z}...
AbstractFor a d-dimensional random field X(t) define the occupation measure corresponding to the lev...
AbstractOur primary aim is to “build” versions of generalised Gaussian processes from simple, elemen...
AbstractWe consider Dynkin's polynomials of the occupation field ⋮Tn⋮ for a 2-dimensional Brownian m...
AbstractLet p(t, x, y) be a symmetric transition density with respect to a σ-finite measure m on (E,...
AbstractIn a recent paper Brydges, Fröhlich, and Spencer have successfully applied Markov chains to ...
For a stationary random field $(X_j)_{j\in\Z^d}$ and some measure m on $\R^d$, we consider the set-i...
summary:We prove a polynomial growth estimate for random fields satisfying the Kolmogorov continuity...
summary:We prove a polynomial growth estimate for random fields satisfying the Kolmogorov continuity...
For a stationary random field $(X_j)_{j\in\Z^d}$ and some measure m on $\R^d$, we consider the set-i...
For a stationary random field $(X_j)_{j\in\Z^d}$ and some measure m on $\R^d$, we consider the set-i...
For a stationary random field $(X_j)_{j\in\Z^d}$ and some measure m on $\R^d$, we consider the set-i...
AbstractOur primary aim is to “build” versions of generalised Gaussian processes from simple, elemen...