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  • Search: subject:"Uniform prior"
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Year of publication
Subject
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Bayesian 2 SVARs 2 sign restrictions 2 uniform prior 2 Bayes-Statistik 1 Bayesian inference 1 G-prior 1 Geldpolitik 1 Generalized linear model 1 Markov chain Monte Carlo 1 Monetary policy 1 Schock 1 Shock 1 Theorie 1 Theory 1 Uniform prior 1 VAR model 1 VAR-Modell 1
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Online availability
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Free 2 Undetermined 1
Type of publication
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Book / Working Paper 2 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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English 2 Undetermined 1
Author
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Arias, Jonas E. 2 Rubio-Ramírez, Juan Francisco 2 Waggoner, Daniel F. 2 Daniels, M.J. 1 Wang, Y. 1
Published in...
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Journal of Multivariate Analysis 1 Working Paper 1 Working papers / Federal Reserve Bank of Atlanta 1
Source
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ECONIS (ZBW) 1 EconStor 1 RePEc 1
Showing 1 - 3 of 3
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Uniform priors for impulse responses
Arias, Jonas E.; Rubio-Ramírez, Juan Francisco; … - 2023
vector autoregressions on the grounds that the uniform prior over the set of orthogonal matrices could be nonuniform for … focus is on joint inference, the uniform prior over the set of orthogonal matrices is not only sufficient but also necessary …
Persistent link: https://www.econbiz.de/10014388427
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Cover Image
Uniform priors for impulse responses
Arias, Jonas E.; Rubio-Ramírez, Juan Francisco; … - 2023
vector autoregressions on the grounds that the uniform prior over the set of orthogonal matrices could be nonuniform for … focus is on joint inference, the uniform prior over the set of orthogonal matrices is not only sufficient but also necessary …
Persistent link: https://www.econbiz.de/10014368558
Saved in:
Cover Image
Bayesian modeling of the dependence in longitudinal data via partial autocorrelations and marginal variances
Wang, Y.; Daniels, M.J. - In: Journal of Multivariate Analysis 116 (2013) C, pp. 130-140
Many parameters and positive-definiteness are two major obstacles in estimating and modeling a correlation matrix for longitudinal data. In addition, when longitudinal data is incomplete, incorrectly modeling the correlation matrix often results in bias in estimating mean regression parameters....
Persistent link: https://www.econbiz.de/10011041927
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