An Efficient Approach to Analyzing State-Space Representations

Joint with: Hariharan Dharmarajan, Roman Liesenfeld and Jean-Francois Richard

We develop a numerical procedure that facilitates efficient likelihood evaluation and filtering in applications involving non-linear and non-Gaussian state-space models. The procedure approximates necessary integrals using continuous approximations of target densities. Construction is achieved via efficient importance sampling, and approximating densities are adapted to fully incorporate current information.

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For more information, contact Frank Schorfheide.