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. Platform: |
Size: 181404 |
Author:阳关 |
Hits:
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 |
Hits:
Description: 使用R语言的马尔科夫链蒙特卡洛模拟（MCMC）源代码程序。-R languages using Markov chain Monte Carlo simulation (MCMC) procedures for source code. Platform: |
Size: 447488 |
Author:左秀霞 |
Hits:
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 |
Hits:
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 |
Hits:
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 |
Hits:
Description: c语言编写的蒙特卡洛仿真软件，可以用于进行标准的和马尔科夫链蒙特卡洛模拟-MCSim is a general purpose modeling and simulation program which can performs
"standard" or "Markov chain" Monte Carlo simulations. Platform: |
Size: 1216512 |
Author:wen |
Hits:
Description: 此为一篇介绍mcmc方法的外文文献 非常适合刚刚接触mcmc方法的初学者-This paper introduces the readers of the Proceedings
to an important class of computer based simulation
techniques known as Markov chain Monte Carlo
(MCMC) methods. General properties characterizing
these methods will be discussed, but the main emphasis
will be placed on one MCMC method known as the
Gibbs sampler. The Gibbs sampler permits one to simulate
realizations from complicated stochastic models in
high dimensions by making use of the model’s associated
full conditional distributions, which will generally have
a much simpler and more manageable form. In its most
extreme version, the Gibbs sampler reduces the analysis
of a complicated multivariate stochastic model to the
consideration of that model’s associated univariate full
conditional distributions. Platform: |
Size: 464896 |
Author:long li |
Hits:
Description: MCMC方法就是*构造合适的马尔科夫链进行抽样而使用蒙特卡洛方法进行积分计算,既然马尔科夫链可以收敛到平稳分布。我们可以建立一个以π为平稳分布的马尔科夫链，对这个链运行足够长时间之后，可以达到平稳状态。此时马尔科夫链的值就相当于在分布π(x)中抽取样本。利用马尔科夫链进行随机模拟的方法就是MCMC。(MCMC method is * construct appropriate sampling of markov chain and USES the monte carlo method for integral calculation, since markov chain can converge to the stationary distribution.We can set up a PI for a smooth distribution of markov chain, the chain operation after long enough, can reach steady state.The value of markov chain is equivalent to draw samples in the distribution of the PI (x).By using the method of markov chain of stochastic simulation is MCMC.) Platform: |
Size: 16384 |
Author:杨彩
|
Hits:
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。(The MCMC method is an important simulation method. The research of Markov chain Monte Carlo:MCMC (Markov) has opened up a broad prospect for the establishment of a practically applicable statistical model. Since 90s, many application problems have been difficult to analyze the complexity of the analysis objects and to identify the structure of the model correctly. Now, according to the MCMC theory, MCMC simulation can be done by using special statistical software to solve many complex problems. In addition, thanks to the application of MCMC theory, Bias's (Bayes) statistics has been revived again, and the statistical method which was previously considered impossible to carry out the calculation became very easy.) Platform: |
Size: 15360 |
Author:me_english |
Hits:
Description: 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.) Platform: |
Size: 15360 |
Author:zszhg |
Hits:
Search - markov chain monte carlo simulation