图 书 馆
对于ML II型参数估计的非线性扩散的一种有效的蒙特卡洛算法An efficient Monte-Carlo algorithm for the ML-Type II parameter estimation of nonlinear diffusions |
|
| 课程网址: | http://videolectures.net/aispds08_shen_emca/ |
| 主讲教师: | Yuan Shen |
| 开课单位: | 阿斯顿大学 |
| 开课时间: | 2008-08-05 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The mathematical framework of non-linear diffusions has been playing an important role in modelling natural phenomena. Recently, much efforts have been made in developing inferential methods for such stochastic dynamical systems. Both state- and parameter estimation are of interests. The state-of-art Hybrid-Monte Carlo method has been applied to state estimation of non-linear diffusions. For parameter estimation, the data augmentation strategy is often adopted. Accordingly, state and parameters are sampled in a Gibbs-sampler setting. However, it has been reported that such a Monte-Carlo algorithm has very poor mixing property. This is due to strong correlations between state and parameter samples. In this paper, we propose a maximal likelihood (ML) type II approach to parameter estimation. Equipped with the Wang-Landau algorithm from statistical physics, the novel algorithm is shown to be both accurate and efficient. |
| 关 键 词: | ML II型参数; 非线性扩散; 蒙特卡洛算法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-10-31：lxf |
| 阅读次数: | 77 |