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Fast Efficient Importance Sampling by State Space Methods

Koopman, Siem Jan - 2014

We show that efficient importance sampling for nonlinear non-Gaussian state space models can be implemented by … simple and fast method for efficient importance sampling. A simulation study and empirical illustration provide some evidence …

Persistent link: https://www.econbiz.de/10013066727

ML-estimation of sampled stochastic differential equations

Singer, Hermann - 2009

Persistent link: https://www.econbiz.de/10015205727

Simulated maximum likelihood for continuous-discrete state space models using Langevin importance sampling

Singer, Hermann - 2016

Persistent link: https://www.econbiz.de/10015205868

Joint Bayesian analysis of parameters and states in nonlinear, non-Gaussian state space models

Barra, István; Hoogerheide, Lennart; Koopman, Siem Jan; … - 2014

We propose a new methodology for designing flexible proposal densities for the joint posterior density of parameters and states in a nonlinear non-Gaussian state space model. We show that a highly efficient Bayesian procedure emerges when these proposal densities are used in an independent...

Persistent link: https://www.econbiz.de/10010399681

ML-estimation of sampled stochastic differential equations

Singer, Hermann - 2009

Persistent link: https://www.econbiz.de/10003876985

On importance sampling for state space models

Jungbacker, Borus; Koopman, Siem Jan - 2005

Persistent link: https://www.econbiz.de/10003248123

Numerically accelerated importance sampling for nonlinear non-Gaussian state space models

Koopman, Siem Jan; Lucas, André; Scharth, Marcel - 2012

refer to our new method as numerically accelerated importance sampling. The method is computationally and numerically …-off encountered by other sampling methods. An elaborate simulation study and an empirical application for U.S. stock returns reveal …

Persistent link: https://www.econbiz.de/10011386179

Langevin and Kalman importance sampling for nonlinear continuous-discrete state space models

Singer, Hermann - 2017

Persistent link: https://www.econbiz.de/10011619759

Simulated maximum likelihood for continuous-discrete state space models using Langevin importance sampling

Singer, Hermann - 2016

Persistent link: https://www.econbiz.de/10011569084

Maximum likelihood estimation of continuous-discrete state-space models : Langevin path sampling vs. numerical integration

Singer, Hermann - 2016

Persistent link: https://www.econbiz.de/10011569146