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arXiv 2003.08544math.PRmath.STstat.TH
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随机混杂系统的EM算法

EM algorithm for stochastic hybrid systems

Masaaki Fukasawa

摘要:

随机混合系统,也称为切换扩散,是一个连续时间马尔可夫过程,其状态空间由离散和连续部分组成。我们考虑离散状态转移的Q矩阵和扩散部分的漂移系数的参数估计。首先,我们推导出连续时间样本路径完全观测下的似然函数。然后,将Elliott等人(Hidden Markov Models,Springer,1995)提出的隐马尔可夫模型的有限维滤波器推广到随机混合系统,推导了部分观测下的似然函数和EM算法,其中连续状态在时间上被连续监测,而离散状态不可观测.

英文摘要:

A stochastic hybrid system, also known as a switching diffusion, is a continuous-time Markov process with state space consisting of discrete and continuous parts. We consider parametric estimation of theQmatrix for the discrete state transitions and of the drift coefficient for the diffusion part. First, we derive the likelihood function under the complete observation of a sample path in continuous-time. Then, extending a finite-dimensional filter for hidden Markov models developed by Elliott et al. (Hidden Markov Models, Springer, 1995) to stochastic hybrid systems, we derive the likelihood function and the EM algorithm under a partial observation where the continuous state is monitored continuously in time, while the discrete state is unobserved.

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