Add to ORKGAbstract- At the first time the statistical description of the Sampling-Reconstruction Procedure of Markov Chains with continuous time and with an arbitrary number of states is given. The analytic expression for the conditional probability density of the jump time moment is obtained. The methodology of the sampling interval choice is suggested. One illustrative example is considered. Key-Words. Sampling, reconstruction, error, Markov chain with continuous tim
Given a Markov process with state space {0, 1} we treat parameter estimation of the transition inten...
Markov jump processes (or continuous-time Markov chains) are a simple and important class of continu...
Monte Carlo methods have found widespread use among many disciplines as a way to simulate random pro...
We introduce a family of generalized-method-of-moments estimators of the pa-rameters of a continuous...
The parameter estimation problem for a Markov jump process sampled at equidistant time points is con...
International audienceModel checking real time properties on probabilistic systems requires computin...
Markov jump processes (or continuous-time Markov chains) are a simple and important class of continu...
Markov chain sampling has received considerable attention in the recent literature, in particular in...
Markov chain sampling has recently received considerable attention in particular in the context of B...
In this thesis we study basic statistical methods in Markov chains. In the case of discrete time, th...
In this thesis we study basic statistical methods in Markov chains. In the case of discrete time, th...
Markov jump processes (or continuous-time Markov chains) are a simple and important class of continu...
In this paper we study the (classical) problem of reconstructing a continuous-time signal from its s...
In many domains where mathematical modelling is applied, a deterministic description of the system a...
Markov jump processes (or continuous-time Markov chains) are a simple and important class of continu...
Given a Markov process with state space {0, 1} we treat parameter estimation of the transition inten...
Markov jump processes (or continuous-time Markov chains) are a simple and important class of continu...
Monte Carlo methods have found widespread use among many disciplines as a way to simulate random pro...
We introduce a family of generalized-method-of-moments estimators of the pa-rameters of a continuous...
The parameter estimation problem for a Markov jump process sampled at equidistant time points is con...
International audienceModel checking real time properties on probabilistic systems requires computin...
Markov jump processes (or continuous-time Markov chains) are a simple and important class of continu...
Markov chain sampling has received considerable attention in the recent literature, in particular in...
Markov chain sampling has recently received considerable attention in particular in the context of B...
In this thesis we study basic statistical methods in Markov chains. In the case of discrete time, th...
In this thesis we study basic statistical methods in Markov chains. In the case of discrete time, th...
Markov jump processes (or continuous-time Markov chains) are a simple and important class of continu...
In this paper we study the (classical) problem of reconstructing a continuous-time signal from its s...
In many domains where mathematical modelling is applied, a deterministic description of the system a...
Markov jump processes (or continuous-time Markov chains) are a simple and important class of continu...
Given a Markov process with state space {0, 1} we treat parameter estimation of the transition inten...
Markov jump processes (or continuous-time Markov chains) are a simple and important class of continu...
Monte Carlo methods have found widespread use among many disciplines as a way to simulate random pro...