Results 11 to 20 of about 771,482 (302)
Journal 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
Future Internet, 2023 In this paper we consider the research and development of classifiers that are trained to predict the task solved by source code. Possible applications of such task detection algorithms include method name prediction, hardware–software partitioning ...
Artyom V. Gorchakov +2 more
doaj +1 more source
Putting Markov Chains Back into Markov Chain Monte Carlo [PDF]
Journal 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
Predictions with Markov Chains
, 2022 Predictions with Markov ...
Paul A. Gagniuc (1818325)
core +1 more source
CLTs and asymptotic variance of time-sampled Markov chains [PDF]
, 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
Parametric Markov Chains: PCTL Complexity and Fraction-free Gaussian Elimination [PDF]
Electronic Proceedings in Theoretical Computer Science, 2017 Parametric Markov chains have been introduced as a model for families of stochastic systems that rely on the same graph structure, but differ in the concrete transition probabilities. The latter are specified by polynomial constraints for the parameters.
Lisa Hutschenreiter +2 more
doaj +1 more source
A Definition Scheme for Quantitative Bisimulation [PDF]
Electronic Proceedings in Theoretical Computer Science, 2015 FuTS, state-to-function transition systems are generalizations of labeled transition systems and of familiar notions of quantitative semantical models as continuous-time Markov chains, interactive Markov chains, and Markov automata.
Diego Latella +2 more
doaj +1 more source
Metastable Markov chains [PDF]
53rd IEEE Conference on Decision and Control, 2014 In this paper, we discuss the dynamics of metastable systems. Such systems exhibit interesting long-living behaviors from which they are guaranteed to inevitably escape (e.g., eventually arriving at a distinct failure or success state). At the heart of this work, we emphasize (1) that for our goals, hybrid systems can be approximated as Markov Decision
Cenk Oguz Saglam, Katie Byl
openaire +2 more sources
Electronic Journal of Probability, 2023 36 pages, 9 ...
Defant, Colin, Li, Rupert
openaire +3 more sources
Optimal control of multiple Markov-switching stochastic systems with numerical applications
Results in Control and Optimization, 2022 In this article the authors set up an optimal control framework for a hybrid stochastic system with dual or multiple Markov switching diffusion processes, while Markov chains governing these switching diffusions are not identical as assumed in the ...
Jianmin Shi
doaj +1 more source