Description: Sequential Monte Carlo without Likelihoods
粒子滤波不用似然函数的情况下
本文摘要:Recent new methods in Bayesian simulation have provided ways of evaluating posterior distributions
in the presence of analytically or computationally intractable likelihood functions.
Despite representing a substantial methodological advance, existing methods based on rejection
sampling or Markov chain Monte Carlo can be highly inefficient, and accordingly
require far more iterations than may be practical to implement. Here we propose a sequential
Monte Carlo sampler that convincingly overcomes these inefficiencies. We demonstrate
its implementation through an epidemiological study of the transmission rate of tuberculosis.-Sequential Monte Carlo without Likelihoods Particle Filtering likelihood function do not have the circumstances of this article Abstract: Recent new methods in Bayesian simulation have provided ways of evaluating posterior distributionsin the presence of analytically or computationally intractable likelihood functions.Despite representing a substantial methodological advance, existing methods based on rejectionsampling or Markov chain Monte Carlo can be highly inefficient, and accordinglyrequire far more iterations than may be practical to implement. Here we propose a sequentialMonte Carlo sampler that convincingly overcomes these inefficiencies. We demonstrateits implementation through an epidemiological study of the transmission rate of tuberculosis . Platform: |
Size: 181248 |
Author:阳关 |
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Description: A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces Platform: |
Size: 8192 |
Author:曹大群 |
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Description: 本源码是基于Markov chain Monte Carlo (MCMC)的Bayesian inference工具包,其中包括MCMC采样，基于MCMC的高斯分类，同时描述了采样的一些方法。其中还有使用文档-toolbox is a collection of Matlab functions for Bayesian inference
with Markov chain Monte Carlo (MCMC) methods Platform: |
Size: 11885568 |
Author:吴晓明 |
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Description: 以“一主三从”主从多机通信系统为物理模型，研究应用马尔可夫链建立仿真算法及蒙特卡洛法建立了数学模型，通过将完整的系统元件化，并对每个元件创立各自的状态转移机模型，仿真运行状态，实现了对于这一通信系统的可靠性建模评估。-" One the main three from the" master-slave multi-communication system for the physical model to study the application of Markov chain Monte Carlo simulation algorithm and the mathematical model established through the will of a complete system components, and the creation of each component their respective state transition model, the simulation run, and the realization of a communication system for the assessment of the reliability of modeling. Platform: |
Size: 17408 |
Author:pobenliu |
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Description: 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. Platform: |
Size: 3072 |
Author:meysa |
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Description: the book <<Simulation and Monte Carlo With applications in finance and MCMC >> about MONte carlo method applying to finance problem and markov chain and markov decision process. Platform: |
Size: 3390464 |
Author:胡桃 |
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Description: 北大于江生教授有关蒙特卡洛方法和马尔科夫链的两个PPT（PDF格式）：An Introduction to MCMC for Machine Learning、Monte Carlo统计方法。共396页-Peking University Professor Yu Jiangsheng on Markov chain Monte Carlo method and the two PPT (PDF format): An Introduction to MCMC for Machine Learning, Monte Carlo statistical methods. A total of 396 Platform: |
Size: 2371584 |
Author:dengyue |
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Description: Markov Chain Monte Carlo Innovations And Applications电子书-Book: Markov Chain Monte Carlo Innovations And Applications Platform: |
Size: 3663872 |
Author:刘军 |
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Description: 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-MCMC method is an important simulation methods, Markov chain Mengtekaer theory (Markov chain Monte Carlo: MCMC) research on the establishment of the practical application of the statistical model can be opened up broad prospects. Since the 90' s, there are a lot of application problems are more complex object model structure with the correct identification difficult. Now under the MCMC theory, through the use of special statistical software MCMC simulation can solve many complex problems. In addition, thanks to the use of MCMC theory makes Bayesian (Bayes) statistics have been re-revival in the past that were considered impossible calculation of statistical methods is very easy to become a Platform: |
Size: 2323456 |
Author:曹哥 |
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Description: MARKOV CHAIN MONTE CARLO算法原理及其实际应用-AN INTRODUCTION TO MARKOV CHAIN MONTE CARLO METHODS AND THEIR ACTUARIAL APPLICATIONS Platform: |
Size: 465920 |
Author:yy |
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Description: 基于马尔可夫链的蒙特卡洛方法在matlab中的实现程序-Based on markov chain monte carlo method is implemented in the matlab program Platform: |
Size: 17408 |
Author:孙彬 |
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Search - Markov Chain Monte Carlo