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
This paper investigates stochastic finite matrices and the corresponding finite Markov chains constr...
The Meixner process is a special type of Levy process which origi-nates from the theory of orthogona...
martingale polynomials, chaos representation property. We extend to matrix-valued stochastic process...
AbstractMarkov processes which are reversible with either Gamma, Normal, Poisson or Negative Binomia...
Markov processes which are reversible with either Gamma, Normal, Poisson or Negative Binomial statio...
AbstractWe describe and investigate a class of Markovian models based on a form of “dynamic occupanc...
We consider a multivariate version of the so-called Lancaster problem of characterizing canonical c...
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 ...
33International audienceWe study a family of bivariate orthogonal polynomials associated to the delt...
AbstractWe study birth and death processes with linear rates λn = n + α + c + 1, μn + 1 = n + c, n ⩾...
The aim of this paper is to study some continuous-time bivariate Markov processes arising from group...
AbstractWe obtain the explicit Karhunen–Loeve decomposition of a Gaussian process generated as the l...
We consider sequences of polynomials that are defined by a three-terms recurrence relation and ortho...
AbstractWe explain how an inner product derived from a perturbation of a weight function by the addi...
This paper investigates stochastic finite matrices and the corresponding finite Markov chains constr...
The Meixner process is a special type of Levy process which origi-nates from the theory of orthogona...
martingale polynomials, chaos representation property. We extend to matrix-valued stochastic process...
AbstractMarkov processes which are reversible with either Gamma, Normal, Poisson or Negative Binomia...
Markov processes which are reversible with either Gamma, Normal, Poisson or Negative Binomial statio...
AbstractWe describe and investigate a class of Markovian models based on a form of “dynamic occupanc...
We consider a multivariate version of the so-called Lancaster problem of characterizing canonical c...
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 ...
33International audienceWe study a family of bivariate orthogonal polynomials associated to the delt...
AbstractWe study birth and death processes with linear rates λn = n + α + c + 1, μn + 1 = n + c, n ⩾...
The aim of this paper is to study some continuous-time bivariate Markov processes arising from group...
AbstractWe obtain the explicit Karhunen–Loeve decomposition of a Gaussian process generated as the l...
We consider sequences of polynomials that are defined by a three-terms recurrence relation and ortho...
AbstractWe explain how an inner product derived from a perturbation of a weight function by the addi...
This paper investigates stochastic finite matrices and the corresponding finite Markov chains constr...
The Meixner process is a special type of Levy process which origi-nates from the theory of orthogona...
martingale polynomials, chaos representation property. We extend to matrix-valued stochastic process...