搜索结果: 16-30 共查到“统计学 Monte Carlo”相关记录52条 . 查询时间(0.153 秒)
A population Monte Carlo scheme with transformed weights and its application to stochastic kinetic models
Population Monte Carlo importance sampling degeneracy of importance weights stochastic kinetic models
2012/9/18
This paper addresses the problem of Monte Carlo approximation of posterior probability distributions. In particular, we have considered a recently proposed technique known as population Monte Carlo (P...
Guaranteed Conservative Fixed Width Confidence Intervals Via Monte Carlo Sampling
Guaranteed Conservative Fixed Width Confidence Intervals Monte Carlo Sampling
2012/9/17
Monte Carlo methods are used to approximate the means,? of random variablesY, whose distributions are not known explicitly. The key idea is that the
average of a random sample,Y1,...,Yn, tends to 礱sn...
Exact Hamiltonian Monte Carlo for Truncated Multivariate Gaussians
Markov Chain Monte Carlo Hamiltonian Monte Carlo Truncated Multivariate Gaus-sians
2012/9/17
We present a Hamiltonian Monte Carlo algorithm to sample from multivariate Gaussian distri-butions in which the target space is constrained by linear and quadratic inequalities or products thereof. Th...
Adaptive Markov Chain Monte Carlo for Auxiliary Variable Method and Its Application to Parallel Tempering
Adaptive Markov Chain Monte Carlo Auxiliary Variable Method Parallel Tempering Conver-gence
2012/9/19
Auxiliary variable methods such as the Parallel Tempering and the cluster Monte Carlo methods generate samples that follow a target distri-bution by using proposal and auxiliary distributions.In sampl...
On nonlinear Markov chain Monte Carlo
Foster–Lyapunov condition interacting Markov chains nonlinear Markov kernels
2011/7/19
Let $\mathscr{P}(E)$ be the space of probability measures on a measurable space $(E,\mathcal{E})$. In this paper we introduce a class of nonlinear Markov chain Monte Carlo (MCMC) methods for simulatin...
Sequential Monte Carlo EM for multivariate probit models
Maximum likelihood Multivariate probit Monte Carlo EM adaptive sequential Monte Carlo
2011/7/19
A Monte Carlo EM algorithm is considered for the maximum likelihood estimation of multivariate probit models.
Split Hamiltonian Monte Carlo
Markov chain Monte Carlo Hamiltonian dynamics Bayesian analysis
2011/7/6
We show how the Hamiltonian Monte Carlo algorithm can sometimes be speeded up by "splitting" the Hamiltonian in a way that allows much of the movement around the state space to be done at low computat...
Monte Carlo algorithms for model assessment via conflicting summaries
Metropolis-Hastings Sequential Monte Carlo model choice
2011/7/6
The development of statistical methods and numerical algorithms for model choice is vital to many real-world applications. In practice, the ABC approach can be instrumental for sequential model design...
Markov Chain Monte Carlo Based on Deterministic Transformations
Geostatistics High dimension Inverse transfromation Jacobian
2011/7/6
In this article we propose a novel MCMC method based on deterministic transformations T : X x D --> X where X is the state-space and D is some set which may or may not be a subset of X. We refer to ou...
Monte Carlo Algorithms for the Partition Function and Information Rates of Two-Dimensional Channels
Two-dimensional channels constrained channels partition function Gibbs sampling importance sampling factor graphs sum-product message passing capacity information rate
2011/6/21
The paper proposes Monte Carlo algorithms for
the computation of the information rate of two-dimensional
source / channel models. The focus of the paper is on binary-input
channels with constraints...
Exact recording of Metropolis-Hastings-class Monte Carlo simulations using one bit per sample
Markov chain Monte Carlo Metropolis-Hastings information theory data representation
2011/6/21
The Metropolis-Hastings (MH) algorithm is the prototype for a class of Markov chain Monte Carlo methods
that propose transitions between states and then accept or reject the proposal. These methods g...
Consistency of Markov chain quasi-Monte Carlo on continuous state spaces
Completely uniformly distributed coupling iterated function mappings Markov chain Monte Carlo
2011/6/17
The random numbers drivingMarkov chainMonte Carlo (MCMC)
simulation are usually modeled as independent U(0, 1) random variables.
Tribble [Markov chain Monte Carlo algorithms using completely
unifor...
Markov chain Monte Carlo for exact inference for diffusions
Exact inference Exact simulation Markov chain Monte Carlo Stochastic differential equa-tion Transition density
2011/3/25
We develop exact Markov chain Monte Carlo methods for discretely-sampled, directly and indirectly observed diffusions. The qualification "exact" refers to the fact that the invariant and limiting dist...
A general purpose variance reduction technique for Markov chain Monte Carlo estimators based on the zero-variance principle introduced in the physics literature by Assaraf and Caffarel (1999, 2003), i...
Weak Convergence of Markov Chain Monte Carlo Methods and its Application to Regular Gibbs Sampler
Methodology (stat.ME) Statistics Theory (math.ST)
2010/12/17
In this paper, we introduce the notion of efficiency (consistency) and examine some asymptotic properties of Markov chain Monte Carlo methods. We apply these results to the Gibbs sampler for independe...