Approximate Bayesian Computation in State Space Models
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Cited by:
- Johan Dahlin & Mattias Villani & Thomas B. Schon, 2015. "Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods," Papers 1506.06975, arXiv.org, revised Jun 2017.
- Christian P. Robert, 2016. "Comment on: Reflections on the Probability Space Induced by Moment Conditions with Implications for Bayesian Inference," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 265-271.
- Ajay Jasra, 2015. "Approximate Bayesian Computation for a Class of Time Series Models," International Statistical Review, International Statistical Institute, vol. 83(3), pages 405-435, December.
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More about this item
Keywords
Likelihood-free methods; latent diffusion models; linear Gaussian state space models; asymptotic sufficiency; unscented Kalman filter; stochastic volatility.;All these keywords.
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2014-12-13 (Econometrics)
- NEP-ETS-2014-12-13 (Econometric Time Series)
- NEP-ORE-2014-12-13 (Operations Research)
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