文章基本信息

标题：Particle-based likelihood inference in partially observed diffusion processes using generalised Poisson estimators
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作者：Jimmy Olsson ; Jonas Ströjby
期刊名称：Electronic Journal of Statistics
印刷版ISSN：1935-7524
出版年度：2011
卷号：5
页码：1090-1122
DOI：10.1214/11-EJS632
语种：English
出版社：Institute of Mathematical Statistics
摘要：This paper concerns the use of the expectation-maximisation (EM) algorithm for inference in partially observed diffusion processes. In this context, a well known problem is that all except a few diffusion processes lack closed-form expressions of the transition densities. Thus, in order to estimate efficiently the EM intermediate quantity we construct, using novel techniques for unbiased estimation of diffusion transition densities, a random weight fixed-lag auxiliary particle smoother, which avoids the well known problem of particle trajectory degeneracy in the smoothing mode. The estimator is justified theoretically and demonstrated on a simulated example.