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Macroeconomic nowcasting using Google probabilities
Koop, Gary; Onorante, Luca - 2019
Persistent link: https://www.econbiz.de/10012244142
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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 for solving non-linear and/or non-Gaussian state space models. We illustrate this with several examples.
Persistent link: https://www.econbiz.de/10011800920
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Forecasting with unobserved components time series models
Harvey, Andrew C. - 2006
Persistent link: https://www.econbiz.de/10003338431
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Particle filtering
Johannes, Michael; Polson, Nicholas G. - In: Handbook of financial time series, (pp. 1015-1029). 2009
Persistent link: https://www.econbiz.de/10003834288
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The use of quadratic filter for the estimation of time-varying β
Gastaldi, M.; Germani, A.; Nardecchia, A. - In: Computational finance and its applications II : [Second …, (pp. 215-224). 2006
Persistent link: https://www.econbiz.de/10003410161
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Modelling the dynamic convergence of business cycles
Lemoine, Matthieu - In: Growth and cycle in the Euro-zone, (pp. 172-182). 2006
Persistent link: https://www.econbiz.de/10003412165
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State space modeling in macroeconomics and finance using SsfPack in S+Finmetrics
Zivot, Eric; Wang, Jeffrey; Koopman, Siem Jan - In: State space and unobserved component models : theory …, (pp. 284-335). 2004
Persistent link: https://www.econbiz.de/10009719920
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Resampling in state space models
Stoffer, David S.; Wall, Kent D. - In: State space and unobserved component models : theory …, (pp. 171-202). 2004
Persistent link: https://www.econbiz.de/10009719925
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An introduction to particle filters
Maskell, Simon - In: State space and unobserved component models : theory …, (pp. 40-71). 2004
Persistent link: https://www.econbiz.de/10009719931
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Robustness analysis of naı̈ve Bayesian classifier-based collaborative filtering
Kaleli, Cihan; Polat, Huseyin - In: E-commerce and web technologies : 14th international …, (pp. 202-209). 2013
Persistent link: https://www.econbiz.de/10010233384