J. Durbin and S.J. Koopman
- Published in print:
- 2012
- Published Online:
- December 2013
- ISBN:
- 9780199641178
- eISBN:
- 9780191774881
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199641178.003.0011
- Subject:
- Mathematics, Probability / Statistics
This chapter develops the methodology of importance sampling based on simulation for the analysis of observations from the non-Gaussian and nonlinear models that were specified in Chapter 9. It shows ...
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This chapter develops the methodology of importance sampling based on simulation for the analysis of observations from the non-Gaussian and nonlinear models that were specified in Chapter 9. It shows that importance sampling methods can be adopted for estimating functions of the state vector and the error variance matrices of the resulting estimates. It develops estimates of conditional densities, distribution functions, and quantiles of interest. Of key importance is the method of estimating unknown parameters by maximum likelihood. The methods are based on standard ideas in simulation methodology and, in particular, importance sampling.Less
This chapter develops the methodology of importance sampling based on simulation for the analysis of observations from the non-Gaussian and nonlinear models that were specified in Chapter 9. It shows that importance sampling methods can be adopted for estimating functions of the state vector and the error variance matrices of the resulting estimates. It develops estimates of conditional densities, distribution functions, and quantiles of interest. Of key importance is the method of estimating unknown parameters by maximum likelihood. The methods are based on standard ideas in simulation methodology and, in particular, importance sampling.
