| 1. | Learning of bayesian network based on mcmc algorithm
算法贝叶斯网络的学习 |
| 2. | Bayesian credibility model for experience rating based on mcmc method
稳态模拟的贝叶斯经验费率厘定信用模型 |
| 3. | Study on the model of loss distribution in pool medical insurance with mcmc
方法研究统筹医疗保险的损失分布模型 |
| 4. | This thesis improves the mcmc method so that it can be adapted to massive datasets " data mining
本文通过改进mcmc算法，使它能够用于巨型数据集的挖掘。 |
| 5. | The computational results indicate that parameters estimation by bayesian method and mcmc sampling has a high precision
计算结果表明采用贝叶斯推理获得的模型参数估计具有很高的精度。 |
| 6. | Mcmc method can reduce the costs of time and space in data mining , but it is impracticable in massive datasets " computation
Mcmc可以减少数据挖掘中的时间和空间开销，但对于巨型数据集， mcmc在计算方面也不切实际。 |
| 7. | Compared to mle procedures , mcmc algorithms are more stable and the problems such as searching the multiple maximal are avoided
Mcmc算法与经典的mle方法相比，它具有更好的稳定性，同时也避免了用mle方法所带来的极值优化的复杂性。 |
| 8. | By combining the chirpogram and the mean likelihood estimation with mrkov chain monte carlo technique , it is shown that accurate estimates can be obtained for chirp signals
此方法将均值似然估计和调频图应用于mcmc中,避免了极大似然估计中的积分运算和多维搜索,减少了计算量。 |
| 9. | 4 ) based on web services flow language and java , the dissertation designs and implements a magent - based cooperative multimedia component ( mcmc ) , which is used to parse and execute web services flow
( 4 )基于web服务流语言和java语言，设计并初步实现了一个基于magent的协作多媒体组件( mcmc ) ，以实现web流的执行与服务。 |
| 10. | Markov chain monte carlo simulation ( mcmc ) was taken to sample the posterior distribution to get the marginal posterior probability function of the parameters , and the statistical quantities such as the mathematic expectation were calculated
通过马尔科夫链蒙特卡罗模拟对后验分布进行了采样，获得了参数的后验边缘概率密度，并在此基础上获得了参数的数学期望等统计量。 |
