In recent work the author proposed a reformed notion of stochastic processes, which in particular removes notorious problems with uncountable time domains. In case of a Polish state space the new stochastic processes are in one-to-one correspondence with the traditional ones. This implies for a stochastic process that the traditional canonical measure on the path space receives a certain distinguished maximal measure extension which has an immense domain. In the present paper we prove, under a certain local compactness condition on the Polish state space and for the time domain [0,∞[, that the maximal domain in question has, for all stochastic processes, three distinguished members: the set of all continuous paths, the set of all path...
Chapter 1 we use a Poisson stochastic measure to establish a method of localizing, and a change of c...
We introduce a domain-theoretic framework for continuous-time, continuous-state stochastic processes...
Many complexity measures are defined as the size of a minimal representation in a specific model cla...
In a recent paper the author used his work in measure and integration to obtain the projective limit...
In recent articles the author used his work in measure and integration to produce a new universal co...
The present article describes the reformulation of certain basic structures, first in measure and in...
AbstractThis paper extends results of Bolthausen and Schmock on the asymptotical behaviour of certai...
AbstractFor strongly ergodic discrete time Markov chains we discuss the possible limits as n→∞ of pr...
In this thesis, we are concerned with the modifications of the stochastic processes and the random p...
summary:Space-time regularity of stochastic convolution integrals J = {\int^\cdot_0 S(\cdot-r)Z(r)W(...
AbstractThe structure of the large values attained by a stationary random process indexed by a one-d...
summary:Using unitary dilations we give a very simple proof of the maximal inequality for a stochast...
AbstractIn this report we relate the property of stochastic boundedness to the existence of stationa...
We consider a family of stochastic processes {X-t(epsilon), t is an element of T} on a metric space ...
Abstract. We introduce the notion of minimality for spectral representations of sum – and max– infin...
Chapter 1 we use a Poisson stochastic measure to establish a method of localizing, and a change of c...
We introduce a domain-theoretic framework for continuous-time, continuous-state stochastic processes...
Many complexity measures are defined as the size of a minimal representation in a specific model cla...
In a recent paper the author used his work in measure and integration to obtain the projective limit...
In recent articles the author used his work in measure and integration to produce a new universal co...
The present article describes the reformulation of certain basic structures, first in measure and in...
AbstractThis paper extends results of Bolthausen and Schmock on the asymptotical behaviour of certai...
AbstractFor strongly ergodic discrete time Markov chains we discuss the possible limits as n→∞ of pr...
In this thesis, we are concerned with the modifications of the stochastic processes and the random p...
summary:Space-time regularity of stochastic convolution integrals J = {\int^\cdot_0 S(\cdot-r)Z(r)W(...
AbstractThe structure of the large values attained by a stationary random process indexed by a one-d...
summary:Using unitary dilations we give a very simple proof of the maximal inequality for a stochast...
AbstractIn this report we relate the property of stochastic boundedness to the existence of stationa...
We consider a family of stochastic processes {X-t(epsilon), t is an element of T} on a metric space ...
Abstract. We introduce the notion of minimality for spectral representations of sum – and max– infin...
Chapter 1 we use a Poisson stochastic measure to establish a method of localizing, and a change of c...
We introduce a domain-theoretic framework for continuous-time, continuous-state stochastic processes...
Many complexity measures are defined as the size of a minimal representation in a specific model cla...