AbstractA general Markov process with innovation is introduced and its properties are studied. Based on the structure of this process, one can develop any autoregressive process of first order minification structure as a special case of this. A necessary and sufficient condition for the general autoregressive process to be stationary is presented. A characterization of semi-Pareto process is obtained
The book presents a coherent treatment of Markov random walks and Markov additive processes together...
Abstract A semi-Markov process is one that changes states in accordance with a Markov chain but take...
AbstractThe paper redefines Markov processes with a random starting time (MPCA) in a more general wa...
A new class of first-order autoregressive minification process which generalizes any autoregressive ...
In this paper we show that particular Gibbs sampler Markov processes can be modified to an autoregre...
We present a stochastic model which yields a stationary Markov process whose invariant distribution ...
This title considers the special of random processes known as semi-Markov processes. These possess t...
We are interested in the existence of pure and stationary optimal strategies in Markov decision proc...
A semi‐Markov process is a generalization of continuous‐time Markov chain, so that the sojourn times...
This paper extends recent ideas for constructing classes of stationary autoregressive processes of o...
This paper is concerned with establishing conditions under which finite (and then countably infinite...
AbstractThis paper is concerned with establishing conditions under which finite (and then countably ...
Abstract A class of semi-Markov process was introduced by Latouche and referred as the semi-Poisson ...
We present three classical methods in the study of dynamic and stationary characteristic of processe...
This paper provides the definitions and basic properties related to a discrete state space semi-Mark...
The book presents a coherent treatment of Markov random walks and Markov additive processes together...
Abstract A semi-Markov process is one that changes states in accordance with a Markov chain but take...
AbstractThe paper redefines Markov processes with a random starting time (MPCA) in a more general wa...
A new class of first-order autoregressive minification process which generalizes any autoregressive ...
In this paper we show that particular Gibbs sampler Markov processes can be modified to an autoregre...
We present a stochastic model which yields a stationary Markov process whose invariant distribution ...
This title considers the special of random processes known as semi-Markov processes. These possess t...
We are interested in the existence of pure and stationary optimal strategies in Markov decision proc...
A semi‐Markov process is a generalization of continuous‐time Markov chain, so that the sojourn times...
This paper extends recent ideas for constructing classes of stationary autoregressive processes of o...
This paper is concerned with establishing conditions under which finite (and then countably infinite...
AbstractThis paper is concerned with establishing conditions under which finite (and then countably ...
Abstract A class of semi-Markov process was introduced by Latouche and referred as the semi-Poisson ...
We present three classical methods in the study of dynamic and stationary characteristic of processe...
This paper provides the definitions and basic properties related to a discrete state space semi-Mark...
The book presents a coherent treatment of Markov random walks and Markov additive processes together...
Abstract A semi-Markov process is one that changes states in accordance with a Markov chain but take...
AbstractThe paper redefines Markov processes with a random starting time (MPCA) in a more general wa...
DOI
Add to ORKG