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  • Search: subject:"Sequential Monte Carlo Nowcasting"
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Year of publication
Subject
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Bayesian filtering 3 Density forecast combination 3 Sequential Monte Carlo Nowcasting 3 Survey forecast 3 Bayesian Filtering 2 Real-time Data 2 density forecast combination 2 real-time data 2 sequential Monte Carlo nowcasting 2 survey forecast 2 Bayes-Statistik 1 Bayesian inference 1 Economic forecast 1 Forecasting model 1 Frühindikator 1 Leading indicator 1 Monte Carlo simulation 1 Monte-Carlo-Simulation 1 Prognoseverfahren 1 Real-time data 1 SMC 1 Statistical distribution 1 Statistische Verteilung 1 Theorie 1 Theory 1 Wirtschaftsprognose 1
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Online availability
All
Free 5
Type of publication
All
Book / Working Paper 5
Type of publication (narrower categories)
All
Working Paper 3 Arbeitspapier 1 Graue Literatur 1 Non-commercial literature 1
Language
All
English 3 Undetermined 2
Author
All
Aastveit, Knut Are 5 Ravazzolo, Francesco 5 Dijk, Herman K. van 3 van Dijk, Herman K. 2
Institution
All
Norges Bank 1 Tinbergen Instituut 1
Published in...
All
Discussion paper / Tinbergen Institute 1 Tinbergen Institute Discussion Paper 1 Tinbergen Institute Discussion Papers 1 Working Paper 1 Working Paper / Norges Bank 1
Source
All
EconStor 2 RePEc 2 ECONIS (ZBW) 1
Showing 1 - 5 of 5
Cover Image
Combined Density Nowcasting in an Uncertain Economic Environment
Aastveit, Knut Are; Ravazzolo, Francesco; van Dijk, … - 2014
We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...
Persistent link: https://www.econbiz.de/10010491381
Saved in:
Cover Image
Combined Density Nowcasting in an Uncertain Economic Environment
Aastveit, Knut Are; Ravazzolo, Francesco; van Dijk, … - 2014
We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...
Persistent link: https://www.econbiz.de/10012143855
Saved in:
Cover Image
Combined Density Nowcasting in an uncertain economic environment
Aastveit, Knut Are; Ravazzolo, Francesco; Dijk, Herman … - Norges Bank - 2014
We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...
Persistent link: https://www.econbiz.de/10011124200
Saved in:
Cover Image
Combined Density Nowcasting in an Uncertain Economic Environment
Aastveit, Knut Are; Ravazzolo, Francesco; Dijk, Herman … - Tinbergen Instituut - 2014
We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...
Persistent link: https://www.econbiz.de/10011272583
Saved in:
Cover Image
Combined density nowcasting in an uncertain economic environment
Aastveit, Knut Are; Ravazzolo, Francesco; Dijk, Herman … - 2014
We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...
Persistent link: https://www.econbiz.de/10010465155
Saved in:
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