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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
MetHast
- 这是蒙特卡洛方法中用Metropolis Hasting方法进行抽样的函数子程序。使用这个方法可以对任意形状的分布进行抽样-This is a Metropolis Hasting Sampling Code. You can sampling any distribution using this.
moyituhuo
- 模拟退火算法的基本思想是从一给定解开始,从邻域中随机产生另一个解,接受Metropolis准则允许目标函数在有限范围内变坏,它由一控制参数t决定,其作用类似于物理过程中的温度T,对于控制参数的每一取值,算法持续进行“产生—判断—接受或舍去”的迭代过程,对应着固体在某一恒定温度下的趋于热平衡的过程,当控制参数逐渐减小并趋于0时,系统越来越趋于平衡态,最后系统状态对应于优化问题的全局最优解,该过程也称为冷却过程,由于固体退火必须缓慢降温,才能使固体在每一温度下都达到热平衡,最终趋于平衡状态,因此控制
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.
gibbs.met_1.1-3.tar
- 马尔可夫链蒙特卡洛算法，由R语言实现，是在Gibbs采样中每步利用Metropolis采样。程序非常清晰，是理解MCMC的好东西-Naive Gibbs Sampling with Metropolis Steps
monituihuo
- 模拟退火fortran程序,可以根据优化函数设置参数-C Simulated annealing is a global optimization method that distinguishes C between different local optima. Starting from an initial point, the C algorithm takes a step and the function is evaluated. When minimizin
metropolis_hastings
- metropolis algorithm code is a useful tool to generate estimated values.
DREAM-V3.0
- 差分进化自适应Metropolis算法Matlab工具箱,是一种马尔科夫链蒙特卡洛(MCMC)工具.带演示例子.-DREAM runs multiple different chains simultaneously for global exploration, and automatically tunes the scale and orientation of the proposal distribution using differential evolution.
MHAlgorithm
- 运用Metropolis-Hasting算法生成任意的二维高斯分布-Use Metropolis-Hasting algorithm to generate an arbitrary two-dimensional Gaussian distribution
Metropolis-Hastings
- 使用metropolis-hastings抽样方法，产生平稳马尔科夫链，R语言实现-Using sampling methods metropolis-hastings, produce smooth Markov chain, R language
模拟退火算法及其在求解TSP中的应用
- 模拟退火算法(Simulated Annealing，SA)最早的思想是由N. Metropolis [1] 等人于1953年提出。1983 年,S. Kirkpatrick 等成功地将退火思想引入到组合优化领域。它是基于Monte-Carlo迭代求解策略的一种随机寻优算法，其出发点是基于物理中固体物质的退火过程与一般组合优化问题之间的相似性。(The earliest idea of Simulated Annealing (SA) was put forward by N. Metropo