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  • Search: subject:"Gamma mixture"
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Year of publication
Subject
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Generalised autoregressive score model 4 Importance sampling 4 Model confidence set 4 Nonlinear state space model 4 Weibull-gamma mixture 4 Prognoseverfahren 2 Theorie 2 Zeitreihenanalyse 2 Zustandsraummodell 2 Forecasting model 1 Monte Carlo simulation 1 Monte-Carlo-Methode 1 Monte-Carlo-Simulation 1 State space model 1 Theory 1 Time series analysis 1 admittance matrix model 1 generalized gamma mixture models 1 harmonic propagation and interaction 1 nonlinear load 1 small-scale wind farm 1
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Online availability
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Free 5
Type of publication
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Book / Working Paper 4 Article 1
Type of publication (narrower categories)
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Working Paper 2 Arbeitspapier 1 Graue Literatur 1 Non-commercial literature 1
Language
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Undetermined 3 English 2
Author
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Koopman, Siem Jan 4 Scharth, Marcel 4 Lucas, Andre 3 Li, Yan 1 Lucas, André 1 Mao, Cheng-Xiong 1 Xie, Guang-Long 1 Zhang, Bu-Han 1
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Institution
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Tinbergen Institute 1 Tinbergen Instituut 1
Published in...
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Tinbergen Institute Discussion Papers 2 Discussion paper / Tinbergen Institute 1 Energies 1 Tinbergen Institute Discussion Paper 1
Source
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RePEc 3 ECONIS (ZBW) 1 EconStor 1
Showing 1 - 5 of 5
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Harmonic Propagation and Interaction Evaluation between Small-Scale Wind Farms and Nonlinear Loads
Xie, Guang-Long; Zhang, Bu-Han; Li, Yan; Mao, Cheng-Xiong - In: Energies 6 (2013) 7, pp. 3297-3322
-Raphson power flow method for the wind farm. Then the generalized gamma mixture models are proposed to study the non … gamma mixture models. Finally, the proposed models and methods are verified through the corresponding simulation models in …
Persistent link: https://www.econbiz.de/10011030831
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Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models
Koopman, Siem Jan; Lucas, Andre; Scharth, Marcel - 2012
We study whether and when parameter-driven time-varying parameter models lead to forecasting gains over observation-driven models. We consider dynamic count, intensity, duration, volatility and copula models, including new specifications that have not been studied earlier in the literature. In...
Persistent link: https://www.econbiz.de/10010326198
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Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models
Koopman, Siem Jan; Lucas, Andre; Scharth, Marcel - Tinbergen Instituut - 2012
Accepted for an article forthcoming in the <I>Review of Economics and Statics</I>. Volume 97, 2015.<P> We study whether and when parameter-driven time-varying parameter models lead to forecasting gains over observation-driven models. We consider dynamic count, intensity, duration, volatility and copula...</p></i>
Persistent link: https://www.econbiz.de/10011256798
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Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models
Koopman, Siem Jan; Lucas, Andre; Scharth, Marcel - Tinbergen Institute - 2012
We study whether and when parameter-driven time-varying parameter models lead to forecasting gains over observation-driven models. We consider dynamic count, intensity, duration, volatility and copula models, including new specifications that have not been studied earlier in the literature. In...
Persistent link: https://www.econbiz.de/10009653053
Saved in:
Cover Image
Predicting time-varying parameters with parameter-driven and observation-driven models
Koopman, Siem Jan; Lucas, André; Scharth, Marcel - 2012
Persistent link: https://www.econbiz.de/10009722696
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