Results 11 to 20 of about 165,146 (318)

Markov Tail Chains [PDF]

open access: yesJournal of Applied Probability, 2014
The extremes of a univariate Markov chain with regularly varying stationary marginal distribution and asymptotically linear behavior are known to exhibit a multiplicative random walk structure called the tail chain. In this paper we extend this fact to Markov chains with multivariate regularly varying marginal distributions in R
Janssen, A., Segers, J.
openaire   +5 more sources

Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions [PDF]

open access: yes, 2014
Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte Carlo
Livingstone, Samuel   +5 more
core   +1 more source

Compositional Approximate Markov Chain Aggregation for PEPA Models [PDF]

open access: yes, 2012
Approximate Markov chain aggregation involves the construction of a smaller Markov chain that approximates the behaviour of a given chain. We discuss two different approaches to obtain a nearly optimal partition of the state-space, based on different ...
Dimitrios Milios   +3 more
core   +1 more source

Putting Markov Chains Back into Markov Chain Monte Carlo [PDF]

open access: yesJournal of Applied Mathematics and Decision Sciences, 2007
Markov chain theory plays an important role in statistical inference both in the formulation of models for data and in the construction of efficient algorithms for inference. The use of Markov chains in modeling data has a long history, however the use of Markov chain theory in developing algorithms for statistical inference has only become popular ...
Richard J. Barker, Matthew R. Schofield
openaire   +1 more source

Small sets and Markov transition densities [PDF]

open access: yes, 2002
The theory of general state-space Markov chains can be strongly related to the case of discrete state-space by use of the notion of small sets and associated minorization conditions. The general theory shows that small sets exist for all Markov chains on
Montana, Giovanni   +2 more
core   +1 more source

CLTs and asymptotic variance of time-sampled Markov chains [PDF]

open access: yes, 2011
For a Markov transition kernel P and a probability distribution μ on nonnegative integers, a time-sampled Markov chain evolves according to the transition kernel Pμ = Σkμ(k)Pk.
Łatuszyński, Krzysztof   +3 more
core   +1 more source

Perturbed Markov chains [PDF]

open access: yesJournal of Applied Probability, 2003
We study irreducible time-homogenous Markov chains with finite state space in discrete time. We obtain results on the sensitivity of the stationary distribution and other statistical quantities with respect to perturbations of the transition matrix. We define a new closeness relation between transition matrices, and use graph-theoretic techniques, in ...
Eilon Solan, Nicolas Vieille
openaire   +7 more sources

Decisive Markov Chains [PDF]

open access: yesLogical Methods in Computer Science, 2007
We consider qualitative and quantitative verification problems for infinite-state Markov chains. We call a Markov chain decisive w.r.t. a given set of target states F if it almost certainly eventually reaches either F or a state from which F can no longer be reached.
Abdulla, Parosh Aziz   +2 more
openaire   +5 more sources

Constraint Markov Chains

open access: yesTheoretical Computer Science, 2011
The article introduces constraint Markov chains as a new tool for specification. They are a generalization of interval Markov chains. Interval Markov chains extend Markov chains by labeling transitions with intervals, implying that each transition probability needs to be within the according interval.
Caillaud, Benoit   +5 more
openaire   +4 more sources

Distributed Markov Chains [PDF]

open access: yes, 2015
The formal verification of large probabilistic models is challenging. Exploiting the concurrency that is often present is one way to address this problem. Here we study a class of communicating probabilistic agents in which the synchronizations determine the probability distribution for the next moves of the participating agents.
Ratul Saha   +4 more
openaire   +2 more sources

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