搜索结果: 1-10 共查到“理论统计学 MCMC”相关记录10条 . 查询时间(0.058 秒)
MCMC methods for Gaussian process models using fast approximations for the likelihood
MCMC methods for Gaussian process models using fast approximations for the likelihood
2013/6/14
Gaussian Process (GP) models are a powerful and flexible tool for non-parametric regression and classification. Computation for GP models is intensive, since computing the posterior density, $\pi$, fo...
MCMC methods for Gaussian process models using fast approximations for the likelihood
MCMC methods for Gaussian process models using fast approximations for the likelihood
2013/6/14
Gaussian Process (GP) models are a powerful and flexible tool for non-parametric regression and classification. Computation for GP models is intensive, since computing the posterior density, $\pi$, fo...
Bayesian Modeling and MCMC Computation in Linear Logistic Regression for Presence-only Data
Bayesian modeling case-control design data augmentation logistic regres-sion Markov Chain Monte Carlo population prevalence presence-only data simulation
2013/6/13
Presence-only data are referred to situations in which, given a censoring mechanism, a binary response can be observed only with respect to on outcome, usually called \textit{presence}. In this work w...
MCMC for non-linear state space models using ensembles of latent sequences
MCMC non-linear state space models ensembles latent sequences
2013/6/13
Non-linear state space models are a widely-used class of models for biological, economic, and physical processes. Fitting these models to observed data is a difficult inference problem that has no str...
Supplement to "Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs"
Sparse graphical model Reversible Markov chain Markov equivalence class
2013/4/27
This supplementary material includes three parts: some preliminary results, four examples, an experiment, three new algorithms, and all proofs of the results in the paper "Reversible MCMC on Markov eq...
Importance Re-sampling MCMC for Cross-Validation in Inverse Problems
Cross-validation Inverse Importance Re-sampling Model fit Re-use
2009/9/22
This paper presents a methodology for cross-validation in the context of Bayesian
modelling of situations we loosely refer to as iverse problems It is motivated by
an example from palaeoclimatology ...
This paper surveys various results about Markov chains on general (non-countable) state spaces. It begins with an introduction to Markov chain Monte Carlo (MCMC) algorithms, which provide the motivati...
A Mixture-Based Approach to Regional Adaptation for MCMC
Adaptive MCMC regional adaptation online EM mixture model
2010/3/19
Recent advances in adaptive Markov chain Monte Carlo (AMCMC) include
the need for regional adaptation in situations when the optimal transition kernel
is different across different regions of the sa...
A Gibbs Sampling Alternative to Reversible Jump MCMC
Gibbs sampler Model switching Variable dimension
2010/3/18
This note presents a simple and elegant sampler which
could be used as an alternative to the reversible jump MCMC methodology.
On the Computational Complexity of MCMC-based Estimators in Large Samples
Markov Chain Monte Carlo Computational Complexity Bayesian Increasing Dimension
2010/4/28
In this paper we examine the implications of the statistical large
sample theory for the computational complexity of Bayesian and quasi-
Bayesian estimation carried out using Metropolis random walks...