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c_inference_ver2.2
- The package includes 3 Matlab-interfaces to the c-code: 1. inference.m An interface to the full inference package, includes several methods for approximate inference: Loopy Belief Propagation, Generalized Belief Propagation, Mean-Field
mcmc_gibbs_intro
- 对马尔科夫链蒙特卡洛模拟和吉布斯采样的一个介绍文章，对了解这些方法非常有用！-We focus here on Markov Chain Monte Carlo (MCMC) methods, which attempt to simulate direct draws from some complex distribution of interest. MCMC approaches are so-named because one uses the previous sample
gibbs_metropol_sampler
- this r code for Gibbs sampler and Metropolis sampler which are two variants of markov chain monte carlo simulators.-this is r code for Gibbs sampler and Metropolis sampler which are two variants of markov chain monte carlo simulators.
OpenBUGS
- 这是国外研究Gibbs采样和Bayesian推理的研究人员写的工具包软件，最新版本为V1.4.3。很适合研究机器学习及其贝叶斯推理的科研人员使用。-The BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian analysis of complex statistical models using Markov chain Monte
Markov-Chain-Monte-Carlo
- Markov Chain Monte Carlo and gibbs sampling
ibp
- Included in this distribution is matlab code to generate posterior samples for linear Gaussian and binary matrix factorization (noisy-or) Indian Buffet Process models. Three different posterior sampling algorithms are provided: Gibbs, reversibl
mcmcexamples
- MCMC（马尔科夫莫特卡洛）方法源代码，MCMC的具体方法有M-H法和Gibbs采样 -Markov Chain Monte Carlo
gibbs
- 吉布斯(Gibbs)抽样方法是 Markov Chain Monte Carlo(MCMC)方法的一种,也是应用最为广泛的一种(The simplest Gibbs sampling is a special case of Metropolis-Hastings algorithm, while the extension of Gibbs sampling can be regarded as a universal sampling system. This system takes a