AbstractMarkov processes which are reversible with either Gamma, Normal, Poisson or Negative Binomial stationary distributions in the Meixner class and have orthogonal polynomial eigenfunctions are characterized as being processes subordinated to well-known diffusion processes for the Gamma and Normal, and birth and death processes for the Poisson and Negative Binomial. A characterization of Markov processes with Beta stationary distributions and Jacobi polynomial eigenvalues is also discussed
It is known that the theory of Markov processes is a rapidly developing field with numerous applica...
AbstractStein's method provides a way of finding approximations to the distribution, ρ say, of a ran...
The Meixner process is a special type of Levy process which origi-nates from the theory of orthogona...
Markov processes which are reversible with either Gamma, Normal, Poisson or Negative Binomial statio...
AbstractMarkov processes which are reversible with either Gamma, Normal, Poisson or Negative Binomia...
AbstractWe describe and investigate a class of Markovian models based on a form of “dynamic occupanc...
martingale polynomials, chaos representation property. We extend to matrix-valued stochastic process...
AbstractWe describe and investigate a class of Markovian models based on a form of “dynamic occupanc...
The aim of this paper is to characterize the one-dimensional stochastic differential equations, for ...
For a series of Markov processes we prove stochastic duality relations with duality functions given ...
For a series of Markov processes we prove stochastic duality relations with duality functions given ...
In this paper, we study strong solutions of some non-local difference–differential equations linked ...
This paper investigates stochastic finite matrices and the corresponding finite Markov chains constr...
We are studying stationary random processes with conditional polynomial moments that allow a continu...
The joint distribution of X and N, where N has a geometric distribution and X is the sum of N IID ex...
It is known that the theory of Markov processes is a rapidly developing field with numerous applica...
AbstractStein's method provides a way of finding approximations to the distribution, ρ say, of a ran...
The Meixner process is a special type of Levy process which origi-nates from the theory of orthogona...
Markov processes which are reversible with either Gamma, Normal, Poisson or Negative Binomial statio...
AbstractMarkov processes which are reversible with either Gamma, Normal, Poisson or Negative Binomia...
AbstractWe describe and investigate a class of Markovian models based on a form of “dynamic occupanc...
martingale polynomials, chaos representation property. We extend to matrix-valued stochastic process...
AbstractWe describe and investigate a class of Markovian models based on a form of “dynamic occupanc...
The aim of this paper is to characterize the one-dimensional stochastic differential equations, for ...
For a series of Markov processes we prove stochastic duality relations with duality functions given ...
For a series of Markov processes we prove stochastic duality relations with duality functions given ...
In this paper, we study strong solutions of some non-local difference–differential equations linked ...
This paper investigates stochastic finite matrices and the corresponding finite Markov chains constr...
We are studying stationary random processes with conditional polynomial moments that allow a continu...
The joint distribution of X and N, where N has a geometric distribution and X is the sum of N IID ex...
It is known that the theory of Markov processes is a rapidly developing field with numerous applica...
AbstractStein's method provides a way of finding approximations to the distribution, ρ say, of a ran...
The Meixner process is a special type of Levy process which origi-nates from the theory of orthogona...