搜索结果: 1-15 共查到“管理学 Markov chains”相关记录31条 . 查询时间(0.167 秒)
We show how to use subgroups of the symmetry group of a reversible Markov chain to give useful bounds on eigenvalues and their multiplicity. We supplement classical representation theoretic tools invo...
Tightness for Non-irreducible Markov Chains
Markov chains stochastic stability tightness Lyapunov functions
2015/7/8
In this paper we develop Foster-type criteria guaranteeing tightness for Markov chains which are not necessarily irreducible. The results include criteria for both tightness of the marginal distributi...
Estimation of Stationary Densities for Markov Chains
Estimation Stationary Densities Markov Chains
2015/7/8
We describe a new estimator of the stationary density of a Markov chain on general state space. The new estimator is easier to compute, converges faster, and empirically gives visually superior estima...
Computing Densities for Markov Chains via Simulation
Markov chain density estimator simulation
2015/7/8
We introduce a new class of density estimators, termed look-ahead density estimators, for performance measures associated with a Markov chain. Look-ahead density estimators are given for both transien...
Hoeffding’s Inequality for Uniformly Recurrent Markov Chains
Hoeffding's inequality Markov chains Large deviations
2015/7/8
We provide a generalization of Hoeffding’s inequality to partial sums that are derived from a uniformly ergodic Markov chain. Our exponential inequality on the deviation of these sums from their expec...
Nested hidden Markov chains for modeling dynamic unobserved heterogeneity in multilevel longitudinal data
composite likelihood EM algorithm latent Markov model pairwise likelihood
2012/9/17
In the context of multilevel longitudinal data, where sample units are collected in clusters, an important aspect that should be accounted for is the unobserved heterogeneity between sample units and ...
We determine an explicit Gr¨obner basis, consisting of linear forms and determi-nantal quadrics, for the prime ideal of Raftery’s mixture transition distribution model for Markov chains. When the stat...
A central limit theorem for adaptive and interacting Markov chains
MCMC interacting MCMC Limit theorems
2011/7/19
Adaptive and interacting Markov Chains Monte Carlo (MCMC) algorithms are a novel class of non-Markovian algorithms aimed at improving the simulation efficiency for complicated target distributions.
An EM Algorithm for Continuous-time Bivariate Markov Chains
Parameter estimation EM algorithm Continuous-time bivariate Markov chain
2011/7/19
We study properties and parameter estimation of finite-state homogeneous continuous-time bivariate Markov chains.
Bayesian analysis of variable-order, reversible Markov chains
Reversibility reinforced random walks variable-order Markov chains Bayesian analysis conjugate priors
2011/6/17
We define a conjugate prior for the reversible Markov chain of
order r. The prior arises from a partially exchangeable reinforced
random walk, in the same way that the Beta distribution arises from
...
Regenerative block empirical likelihood for Markov chains
Nummelin splitting technique time series Empirical Likelihood
2011/3/21
Empirical likelihood is a powerful semi-parametric method increasingly investigated in the literature. However, most authors essentially focus on an i.i.d. setting. In the case of dependent data, the ...
Regenerative block empirical likelihood for Markov chains
Nummelin splitting technique time series Empirical Likelihood MSC codes: 62G05 62F35 62F40
2011/3/23
Empirical likelihood is a powerful semi-parametric method increasingly investigated in the literature. However, most authors essentially focus on an i.i.d. setting. In the case of dependent data, the ...
CLTs and asymptotic variance of time-sampled Markov chains
time-sampled Markov chains Barker’s algo-rithm Metropolis algorithm Central Limit Theorem asymptotic variance variance bounding Markov chains MCMC estimation
2011/3/25
For a Markov transition kernel $P$ and a probability distribution $ \mu$ on nonnegative integers, a time-sampled Markov chain evolves according to the transition kernel $P_{\mu} = \sum_k \mu(k)P^k.$ I...
In this paper, we relate the coupling of Markov chains, at the basis of perfect sampling methods, with damage spreading, which captures the chaotic nature of stochastic dynamics. For two-dimensional ...
Geometric ergodicity for families of homogeneous Markov chains
Homogeneous Markov chain Geometric ergodicity Couplingrenewal processes Lyapunov function Renewal theory
2010/3/11
In this paper we find nonasymptotic exponential upper bounds for
the deviation in the ergodic theorem for families of homogeneous Markov
processes. We find some sufficient conditions for geometric e...