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2018高维统计模型的贝叶斯计算研讨会（Workshop on Bayesian Computation for High-Dimensional Statistical Models）
2018 高维统计模型的贝叶斯计算 研讨会
2017/12/20
In recent years there has been an explosion of complex data-sets in areas as diverse as Bioinformatics, Ecology, Epidemiology, Finance, subsurface Geophysics, Meteorology, and Population genetics. In ...
abc: an R package for Approximate Bayesian Computation (ABC)
abc package Approximate Bayesian Computation
2011/7/7
Many recent statistical applications involve inference under complex models, where it is computationally prohibitive to calculate likelihoods but possible to simulate data.
abc: an R package for Approximate Bayesian Computation (ABC)
an R package pproximate Bayesian Computation
2011/9/14
Background: Many recent statistical applications involve inference under complex models, where it is computationally prohibitive to calculate likelihoods but possible to simulate data. Approximate Bay...
Deviance Information Criteria for Model Selection in Approximate Bayesian Computation
Approximate Bayesian computation evolutionary genetics statistical
2011/6/16
Approximate Bayesian computation (ABC) is a class of algorithmic
methods in Bayesian inference using statistical summaries and computer
simulations. ABC has become popular in evolutionary genetics a...
Exploring the Energy Landscapes of Protein Folding Simulations with Bayesian Computation
Exploring Energy Landscapes Protein Folding Simulations Bayesian Computation
2010/11/15
Nested sampling is a technique developed to explore probability distributions localised in an exponentially small area of the parameter space. The algorithm provides both posterior samples and an est...
Bayesian Cointegrated Vector Autoregression models incorporating Alpha-stable noise for inter-day price movements via Approximate Bayesian Computation
Cointegrated Vector Autoregression -stable Approximate Bayesian Computation
2010/10/21
We consider a statistical model for pairs of traded assets, based on a Cointegrated Vector Auto Regression (CVAR) Model. We extend standard CVAR models to incorporate estimation of model parameters in...
On sequential Monte Carlo，partial rejection control and approximate Bayesian computation
Approximate Bayesian computation Bayesian computation Likelihood free inference Sequential Monte Carlo samplers
2010/4/30
We present a sequential Monte Carlo sampler variant of the partial rejection
control algorithm, and show that this variant can be considered as a sequential
Monte Carlo sampler with a modified mutat...
Nested Sampling for General Bayesian Computation
Bayesian computation evidence marginal likelihood algorithm nest annealing phase change model selection
2009/9/21
Nested sampling estimates directly how the likelihood function relates
to prior mass. The evidence (alternatively the marginal likelihood, marginal den-
sity of the data, or the prior predictive) is...
Bayesian Computation and Model Selection in Population Genetics
Bayesian Computation Model Selection Population Genetics
2010/3/17
Until recently, the use of Bayesian inference in population genetics was lim-
ited to a few cases because for many realistic population genetic models the
likelihood function cannot be calculated an...
Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems
Approximate Bayesian computation scheme parameter inference model selection dynamical systems
2010/3/17
Approximate Bayesian computation methods can be used to evaluate posterior distributions without having to calculate likelihoods. In this paper we discuss and apply an approximate Bayesian computation...