搜索资源列表
mcmc
- 马尔可夫链，蒙特卡洛方法，数值模拟 matlab程序-Markov chain Monte Carlo methods, numerical simulation procedures Matlab
ReversibleJumpMCMCSimulatedAnneaing
- This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global se
automix
- he AutoMix package is a C program for Unix-like systems, implementing the automatic reversible jump MCMC sampler of the same name described in Chapters 4, 5, and 6 of David Hastie s Ph.D. thesis-he AutoMix package is a C program for Unix-l ike s
upf_ekf_ukf_epf_demos
- 关于pf，ekf，ukf，upf，epf，并加上mcmc算法
ssmcmcmatlab
- semi-supervised MCMC classification
A_MCMC_approach_for_Bayesian_super-resolution_imag
- MCMC方法的超分辨paper，此论文是已贝叶斯统计论文为基础，是另一种很有效的sr方法
QHQ++
- the C++ library named QHQ++ which includes four sub libraries QHQc++ (C++ Numerical Library), QHQmcmc++ (MCMC algorithms), QHQsv++ (Stochastic Volatility Model) and QHQyv++ (Yield Curve Modeling).
rjMCMCsa
- On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and
mcmc
- MCMC方法主要是为了解决有些baysian推断中参数期望E(f(v)|D)不能直接计算得到的问题的。 其中v是要估计的参数，D是数据观察值-The concept consists of two parts:markov chain and monte carlo integration。
MCMC
- mcmc学习代码，gibbs抽样,zheng tai fang fa-mcmc,learning programm,gibbs samplers
dream
- 贝叶斯MCMC，Dream算法，可以用来计算不确定性。(This fortran program is a Dream method)
算法
- 马尔科夫蒙特卡洛算法的MATLAB应用示例(code for MCMC in MATLAB)
matlablistings
- 马尔科夫链蒙特卡洛算法简单实例,模式识别，参数识别(mcmc,bayesian,Based on markov chain monte carlo method is implemented in the matlab program)
MH-MCMC
- Metropolis-Hastings算法的R语言实现(Implementation of Metropolis-Hastings algorithm in R language)
二项okkkkkkk
- 运用mcmc方法识别二项分布多变点变点位置及参数(Identification of variable point position and parameter of two distribution points by using MCMC method)
mcmc
- MCMC方法是一种重要的模拟计算方法，马尔可夫链蒙特卡尔理论(Markov chain Monte Carlo：MCMC)的研究对建立可实际应用的统计模型开辟了广阔的前景。90年代以来，很多应用问题都存在着分析对象比较复杂与正确识别模型结构的困难。现在根据MCMC理论，通过使用专用统计软件进行MCMC模拟，可解决许多复杂性问题。此外，得益于MCMC理论的运用，使得贝叶斯(Bayes)统计得到了再度复兴，以往被认为不可能实施计算的统计方法变得是很轻而易举了。(The MCMC method is
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
mcmc的matlab代码
- 马尔科夫链蒙特卡洛模拟，用于金融数学模型的参数估计等作用。(markov chain monte carlo simulation is used to be parameter estimation for financial mathematical models.)
马尔科夫链蒙特卡洛模拟的matlab源代码
- 使用马尔科夫蒙特卡洛方法对非常规的概率密度函数进行样本抽取(use MCMC to draw samples)
MCMC
- 用马尔可夫蒙特卡罗抽样从抽取样本，并拟合总体分布：正态分布、beta分布、t分布(Markov Monte Carlo sampling was used to extract samples and fit the population distribution: normal distribution, beta distribution and t distribution.)