Similar Search Results

Sequential Monte Carlo sampling for state space models

Wüthrich, Mario V. - In: Robustness in econometrics, (pp. 25-50). 2017

The aim of these notes is to revisit sequential Monte Carlo (SMC) sampling. SMC sampling is a powerful simulation tool …

Persistent link: https://www.econbiz.de/10011800920

The Gibbs Sampler with Particle Efficient Importance Sampling for State-Space Models

Grothe, Oliver - 2017

Monte Carlo (MC) approximation of the standard Gibbs procedure which uses sequential MC (SMC) importance sampling inside the … generic and easily implementable SMC approach known as Particle Efficient Importance Sampling (PEIS). By using SMC importance … sampling densities which are approximately fully globally adapted to the targeted density of the states, PEIS can substantially …

Persistent link: https://www.econbiz.de/10012970355

Small area estimation with state-space common factor models for rotating panels

Brakel, Jan A. van den; Krieg, Sabine - 2014

Persistent link: https://www.econbiz.de/10010393950

Empirical Bayes methods for dynamic factor models

Koopman, Siem Jan; Mesters, Geert - 2014

We consider the dynamic factor model where the loading matrix, the dynamic factors and the disturbances are treated as latent stochastic processes. We present empirical Bayes methods that enable the efficient shrinkage-based estimation of the loadings and the factors. We show that our estimates...

Persistent link: https://www.econbiz.de/10010357912

Efficient estimation of conditionally linear and Gaussian state space models

Moura, Guilherme Valle; Turatti, Douglas Eduardo - In: Economics letters 124 (2014) 3, pp. 494-499

Persistent link: https://www.econbiz.de/10010495099

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

Koopman, Siem Jan; Lucas, André; Scharth, Marcel - In: Journal of business & economic statistics : JBES ; a … 33 (2015) 1, pp. 114-127

Persistent link: https://www.econbiz.de/10011389921

On importance sampling for state space models

Jungbacker, Borus; Koopman, Siem Jan - 2005

We consider likelihood inference and state estimation by means of importance sampling for state space models with a … are presented that lead to a more effective implementation of importance sampling for state space models. An illustration …

Persistent link: https://www.econbiz.de/10011348357

Precision-based sampling with missing observations : a factor model application

Hauber, Philipp; Schumacher, Christian - 2021

states and model variables, which is sparse and banded in many economic applications and allows for efficient sampling. The … existing literature on precision-based sampling is focused on complete-data applications, whereas the proposed samplers in this …

Persistent link: https://www.econbiz.de/10012510141

Multi-signal approaches for repeated sampling schemes in inertial sensor calibration

Bakalli, Gaetan; Cuccio, Davide; Radi, Ahmed; … - 2021

Inertial sensor calibration plays a progressively important role in many areas of research among which navigation engineering. By performing this task accurately, it is possible to significantly increase general navigation performance by correctly filtering out the deterministic and stochastic...

Persistent link: https://www.econbiz.de/10012799578

Likelihood inference for dynamic linear models with Markov switching parameters : on the efficiency of the Kim filter

Kim, Young Min; Kang, Kyu Ho - In: Econometric reviews 38 (2019) 10, pp. 1109-1130

Persistent link: https://www.econbiz.de/10012181397