Efficient Likelihood Evaluation of State-Space Representations

DOI10.1093/restud/rds040zbMath1263.91036OpenAlexW2142021412MaRDI QIDQ4922019

Roman Liesenfeld, Hariharan Dharmarajan, David N. DeJong, Guilherme V. Moura, Jean-Francois Richard

Publication date: 28 May 2013

Published in: The Review of Economic Studies (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1093/restud/rds040

zbMATH Keywords

particle filterdynamic stochastic general equilibrium modelefficient importance samplingkernel density approximation

Mathematics Subject Classification ID

Statistical methods; economic indices and measures (91B82)

Related Items (10)

A one‐step‐ahead pseudo‐DIC for comparison of Bayesian state‐space models ⋮ Bandwidth selection in pre-smoothed particle filters ⋮ Maximum likelihood recursive state estimation using the expectation maximization algorithm ⋮ A Survey of Sequential Monte Carlo Methods for Economics and Finance ⋮ Particle efficient importance sampling ⋮ Bayesian inference for nonlinear structural time series models ⋮ Efficient estimation of conditionally linear and Gaussian state space models ⋮ Particle filters for partially-observed Boolean dynamical systems ⋮ Boolean Kalman filter and smoother under model uncertainty ⋮ On particle methods for parameter estimation in state-space models

Uses Software

• nwSpGr

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