Add to ORKGAbstract: Markov chains are useful to model various complex systems. In numerous situations, the underlying Markov chain is subject to changes. For example, states may be added or deleted and transition probabilities perturbed. It is therefore, necessary to ensure the robustness of the system and to estimate the resulting deviation in the characteristics. In this paper we study the sensitivity of finite Markov chains subject to changes in their state space and propose updating formulas and perturbation bounds
communicated by I. Pinelis Abstract. For the distribution of a finite, homogeneous, continuous-time ...
A Markov chain (with a discrete state space and a continuous parameter) is perturbed by forcing a ch...
summary:Sensitivity analysis of irreducible Markov chains considers an original Markov chain with tr...
Markov chains are useful to model various complex systems. In numerous situations, the underlying Ma...
We study irreducible time-homogenous Markov chains with finite state space in discrete time. We obta...
AbstractFor finite irreducible discrete time Markov chains, whose transition probabilities are subje...
Abstract. For many Markov chains of practical interest, the invariant distri-bution is extremely sen...
We provide algorithms to compute the performance derivatives of Markov chains with respect to change...
We obtain results on the sensitivity of the invariant measure and other statistical quantities of a ...
Two fundamental concepts and quantities, realization factors and performance potentials, are introdu...
AbstractThe sensitivity of the unique stationary distribution of a finite Markov chain which has a s...
Dynamical systems are often subject to forcing or changes in their governing parameters and it is of...
Cahier de Recherche du Groupe HEC Paris, n° 757We obtain results on the sensitivity of the invariant...
AbstractA Markov chain (with a discrete state space and a continuous parameter) is perturbed by forc...
AbstractTechniques for updating the stationary distribution of a finite irreducible Markov chain fol...
communicated by I. Pinelis Abstract. For the distribution of a finite, homogeneous, continuous-time ...
A Markov chain (with a discrete state space and a continuous parameter) is perturbed by forcing a ch...
summary:Sensitivity analysis of irreducible Markov chains considers an original Markov chain with tr...
Markov chains are useful to model various complex systems. In numerous situations, the underlying Ma...
We study irreducible time-homogenous Markov chains with finite state space in discrete time. We obta...
AbstractFor finite irreducible discrete time Markov chains, whose transition probabilities are subje...
Abstract. For many Markov chains of practical interest, the invariant distri-bution is extremely sen...
We provide algorithms to compute the performance derivatives of Markov chains with respect to change...
We obtain results on the sensitivity of the invariant measure and other statistical quantities of a ...
Two fundamental concepts and quantities, realization factors and performance potentials, are introdu...
AbstractThe sensitivity of the unique stationary distribution of a finite Markov chain which has a s...
Dynamical systems are often subject to forcing or changes in their governing parameters and it is of...
Cahier de Recherche du Groupe HEC Paris, n° 757We obtain results on the sensitivity of the invariant...
AbstractA Markov chain (with a discrete state space and a continuous parameter) is perturbed by forc...
AbstractTechniques for updating the stationary distribution of a finite irreducible Markov chain fol...
communicated by I. Pinelis Abstract. For the distribution of a finite, homogeneous, continuous-time ...
A Markov chain (with a discrete state space and a continuous parameter) is perturbed by forcing a ch...
summary:Sensitivity analysis of irreducible Markov chains considers an original Markov chain with tr...