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Perfect Sampling of Markov Chains with Piecewise Homogeneous Events
Markov chains perfect sampling queueing systems
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2011/3/2
Perfect sampling is a technique that uses coupling arguments to provide a sample from the stationary distribution of a Markov chain in a nite time without ever computing the distribution.
An algebraic analysis of the two state Markov model on tripod trees
Phylogenetics Identi ability Invariant Two-State-Model
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2011/3/1
Methods of phylogenetic inference use more and more complex models to generate trees from data. However, even simple models and their implications are not fully understood.Here, we investigate the two...
Two Pinning Models with Markov disorder
pinning models statistical mechanics polymers
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2011/2/21
Disordered pinning models deal with the (de)localization tran-sition of a polymer in interaction with a heterogeneous interface. In this paper, we focus on two models where the inhomogeneities at the ...
A Stochastic Markov Model for Coordinated Molecular Motors
Stochastic Markov Model Coordinated Molecular Motors
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2010/12/28
Many cell functions are accomplished thanks to intracellular transport mechanisms of macromolecules along filaments.
Ergodicity of Markov Semigroups with Hörmander type generators in Infinite Dimensions
Ergodicity of Markov Semigroups Hö rmander type generators Infinite Dimensions
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2011/1/17
We develop an effective strategy for proving strong ergodicity of (nonsymmetric)Markov semigroups associated to H¨ormander type generators when the underlying configuration space is infinite dimension...
Numerical methods for the exit time of a piecewise-deterministic Markov process
exit time piecewise deterministic Markov processes quantization
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2011/1/21
We present a numerical method to compute the survival function and the moments of the exit time for a piecewise-deterministic Markov process (PDMP).
Delayed feedback causes non-Markovian behavior of neuronal firing statistics
Delayed feedback non-Markovian behavior neuronal firing statistics
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2011/3/4
The instantaneous state of a neural network consists of both the degree of excitation of each neuron, the network is composed of, and positions of impulses in communication lines between neurons.
Weak Convergence of Markov Chain Monte Carlo Methods and its Application to Regular Gibbs Sampler
Ergodicity Gibbs sampler Large sample theory Markov chain
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2011/3/2
In this paper, we introduce the notion of efficiency (consistency) and examine some asymptotic properties ofMarkov chain Monte Carlo methods. We apply these results to the Gibbs sampler for independen...
An asymptotic approximation of the marginal likelihood for general Markov models
BIC marginal likelihood singular models tree models Bayesian
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2011/1/18
The standard Bayesian Information Criterion (BIC) is derived under regularity conditions which are not always satis ed by the graphical models with hidden variables.
Polygonal Homographic Orbits of the Curved n-Body Problem
Polygonal Homographic Orbits Curved n-Body Problem
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2011/1/20
In the 2-dimensional n-body problem in spaces of constant curvature, 6= 0, with n ≥ 3, we study polygonal homographic solutions.
Poincaré inequality for Markov random fields via disagreement percolation
Poincar´ e inequality weak Poincar´ e inequality Gibbs mea-
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2011/1/20
We consider Markov random fields of discrete spins on the lattice Zd. We use a technique of coupling of conditional distributions. If under the coupling the disagreement cluster is “sufficiently” subc...
Entropy Rate for Hidden Markov Chains with rare transitions
Entropy Rate for Hidden Markov Chains rare transitions
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2011/1/20
We consider Hidden Markov Chains obtained by passing a Markov Chain with rare transitions through a noisy memoryless channel. We obtain asymptotic estimates for the entropy of the resulting Hidden Mar...
The local properties of the Markov processes of Ornstein-Uhlenbeck type
local time Markov process of Ornstein-Uhlenbeck type L´ evy process
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2010/12/6
We prove the existence of a local time, the continuity of the local time about t, and the regular property for a.e. x ∈ R of a Ornstein-Uhlenbeck type {Xt, t ∈ R+} driven by a general L´evy proc...
Martingale problems on Banach spaces -- Existence, uniqueness and the Markov property
Martingale solution strong Markov property stochastic partial differential equation
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2010/12/6
We study (local) martingale problems on a general separable Banach space E and apply our results to stochastic evolution equations. In particular,we prove that if such an equation is well-posed, then ...
Metastability of reversible finite state Markov processes
Metastability Finite state Markov processes Reversibility
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2010/12/9
We prove the metastable behavior of reversible Markov processes on finite state spaces under minimal conditions on the jump rates. To illustrate the result we deduce the metastable behavior of the Isi...