Nous démontrons l’existence de l’exposant persistance log?:=limn?? 1 nlog P?(X0?S,…,Xn?S) pour une classe chaines Markov {Xi}i?0 homogènes en temps avec valeurs dans un espace Polonais, où S est ensemble Borélien et ? distribution initiale. En nous concentrant sur le cas processus type AR(p) ou MA(q) p,q?N d’innovation continue, étudions ? sa continuité par rapport au paramètres des AR MA, S=R?...

abstract stochastic model for synthetic data generation is not available for daily flows of intermittent streams. such a model is required in the planning and operation of structures on an intermittent stream for purposes where short time flow fluctuations are important. in this study a model is developed for such a case. the model consists of four steps: determination of the days on which flow...

Investors use different approaches to select optimal portfolio. so, Optimal investment choices according to return can be interpreted in different models. The traditional approach to allocate portfolio selection called a mean - variance explains. Another approach is Markov chain. Markov chain is a random process without memory. This means that the conditional probability distribution of the nex...

We propose to use a mathematical method based on stochastic comparisons of Markov chains in order to derive performance indice bounds‎. ‎The main goal of this paper is to investigate various monotonicity properties of a single server retrial queue with first-come-first-served (FCFS) orbit and general retrial times using the stochastic ordering techniques‎.

A class of Markov chains we call successively lumpable is specified for which it is shown that the stationary probabilities can be obtained by successively computing the stationary probabilities of a propitiously constructed sequence of Markov chains. Each of the latter chains has a(typically much) smaller state space and this yields significant computational improvements. We discuss how the re...

A parallel composition is defined for Markov reward chains with fast transitions and for discontinuous Markov reward chains. In this setting, compositionality with respect to the relevant aggregation preorders is established. For Markov reward chains with fast transitions the preorders are τ -lumping and τ -reduction. Discontinuous Markov reward chains are ‘limits’ of Markov reward chains with ...

Probabilistic Computation Tree Logic (PCTL) is the established temporal logic for probabilistic verification of discrete-time Markov chains. Probabilistic model checking is a technique that verifies or refutes whether a property specified in this logic holds in a Markov chain. But Markov chains are often infinite or too large for this technique to apply. A standard solution to this problem is t...