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The Gibbs Sampler with Particle Efficient Importance Sampling for State-Space Models
Grothe, Oliver - 2017
We consider Particle Gibbs (PG) as a tool for Bayesian analysis of non-linear non-Gaussian state-space models. PG is a Monte Carlo (MC) approximation of the standard Gibbs procedure which uses sequential MC (SMC) importance sampling inside the Gibbs procedure to update the latent and potentially...
Persistent link: https://www.econbiz.de/10012970355
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The Gibbs sampler with particle efficient importance sampling for state-space models
Grothe, Oliver; Kleppe, Tore Selland; Liesenfeld, Roman - In: Econometric reviews 38 (2019) 10, pp. 1152-1175
Persistent link: https://www.econbiz.de/10012181399
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Bayesian estimation of volatility with moment-based nonlinear stochastic filters
Grothe, Oliver - 2006
Persistent link: https://www.econbiz.de/10013409325
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Risk aversion and flexibility options in electricity markets
Möbius, Thomas; Riepin, Iegor; Müsgens, Felix; … - In: Energy economics 126 (2023), pp. 1-18
Persistent link: https://www.econbiz.de/10014480964