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Filtering via Simulation: Auxiliary Particle Filters

 

作者: MichaelK. Pitt,   Neil Shephard,  

 

期刊: Journal of the American Statistical Association  （Taylor Available online 1999）
卷期: Volume 94, issue 446  

页码: 590-599

 

ISSN:0162-1459

 

年代: 1999

 

DOI:10.1080/01621459.1999.10474153

 

出版商: Taylor & Francis Group

 

关键词: Filtering;Markov chain Monte Carlo;Particle filter;Sampling/importance resampling;Simulation;State space

 

数据来源: Taylor

 

摘要:

This article analyses the recently suggested particle approach to filtering time series. We suggest that the algorithm is not robust to outliers for two reasons: The design of the simulators and the use of the discrete support to represent the sequentially updating prior distribution. Here we tackle the first of these problems.

 

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