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Markov chains (discrete-time Markov processes on discrete state spaces)
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MSC 2010
broader concept
Markov processes
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Markov链(离散状态空间上离散时间Markov过程)
Markov chains (discrete-time Markov processes on discrete state spaces)
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from MSC1991 value of: Markov chains with discrete parameter
from MSC2000 value of: Markov chains with discrete parameter
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60J10
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Subject
of
Convergence of iterates of a transfer operator, application to dynamical systems and to Markov chains
Ergodicity of a certain class of Non Feller Models: Applications to ARCH and Markov switching models
Stationary measures and phase transition for a class of Probabilistic Cellular Automata
Graph fibrations, graph isomorphism, and PageRank
Large deviations and full Edgeworth expansions for finite Markov chains with applications to the analysis of genomic sequences
Weak law of large numbers for some Markov chains along non homogeneous genealogies
The compositional construction of Markov processes II
On absorption times and Dirichlet eigenvalues
Deviation inequalities for bifurcating Markov chains on Galton−Watson tree
http://hub.abes.fr/edp/periodical/ps/2006/volume_10/issue_2006/ps0503/w
Sojourn time in ℤ + for the Bernoulli random walk on ℤ
Transient random walk in ${\mathbb Z}^2$ with stationary orientations
Asymptotic Hölder regularity for the ellipsoid process
Ergodic risk-sensitive control of Markov processes on countable state space revisited
A basic model of mutations
On the generalized Kesten-McKay distributions
The asymptotic shape theorem for the frog model on finitely generated abelian groups
Approximating quasi-stationary distributions with interacting reinforced random walks
Limit behaviour of random walks on ℤ m with two-sided membrane
Strong stationary times for finite Heisenberg walks
Reliable prediction in the Markov stochastic block model
Cutoff for samples of Markov chains
Antiduality and Möbius monotonicity: generalized coupon collector problem
A weak perturbation theory for approximations of invariant measures in M/G/1 model
is
narrower concept
of
Markov processes
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