Abstract

http://ssrn.com/abstract=1509782
 
 

References (29)



 


 



Sequential Inference for Nonlinear Models using Slice Variables


Michael S. Johannes


Columbia Business School - Finance and Economics

Nick Polson


University of Chicago - Booth School of Business

Seung M. Yae


University of Chicago - Booth School of Business

November 19, 2009


Abstract:     
This paper develops particle-based methods for sequential inference in nonlinear models. Sequential inference is notoriously difficult in nonlinear state space models. To overcome this, we use auxiliary state variables to slice out nonlinearities where appropriate. This induces a Fixed-dimension conditional sufficient statistics and, given these, we adapt existing particle learning algorithms to update posterior beliefs about states and parameters. We provide three illustrations. First, a dynamic exponential model with Gaussian errors. Second, a stochastic growth model with nonlinear state evolution and t-distributed errors. Finally, a bivariate radar tracking problem which was originally analyzed in the nonlinear Monte Carlo Filtering literature. In all cases, we illustrate the efficiency of our methodology.

Number of Pages in PDF File: 35

Keywords: Monte Carlo, Particle Filtering, Particle Learning, Nonlinear State Space Model, Slice Variable

JEL Classification: C1, C11, C15

working papers series


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Date posted: November 21, 2009  

Suggested Citation

Johannes, Michael S. and Polson, Nick and Yae, Seung M., Sequential Inference for Nonlinear Models using Slice Variables (November 19, 2009). Available at SSRN: http://ssrn.com/abstract=1509782 or http://dx.doi.org/10.2139/ssrn.1509782

Contact Information

Michael Slater Johannes
Columbia Business School - Finance and Economics ( email )
3022 Broadway
New York, NY 10027
United States

Nick Polson (Contact Author)
University of Chicago - Booth School of Business ( email )
5807 S. Woodlawn Avenue
Chicago, IL 60637
United States
773-702-7513 (Phone)
773-702-0458 (Fax)
Seung Min Yae
University of Chicago - Booth School of Business ( email )
5807 S. Woodlawn Avenue
Chicago, IL 60637
United States
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