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Bayesian nonparametric vector autoregressive models
Kalli, Maria; Griffin, Jim E. - In: Journal of econometrics 203 (2018) 2, pp. 267-282
Persistent link: https://www.econbiz.de/10011974694
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Large Bayesian VARMAs
Chan, Joshua; Eisenstat, Eric; Koop, Gary - In: Journal of econometrics 192 (2016) 2, pp. 374-390
Persistent link: https://www.econbiz.de/10011704723
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A computationally efficient method for vector autoregression with mixed frequency data
Qian, Hang - In: Journal of econometrics 193 (2016) 2, pp. 433-437
Persistent link: https://www.econbiz.de/10011704991
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Nowcasting in a pandemic using non-parametric mixed frequency VARs
Huber, Florian; Koop, Gary; Onorante, Luca; Pfarrhofer, … - In: Journal of econometrics 232 (2023) 1, pp. 52-69
Persistent link: https://www.econbiz.de/10013472832
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Improved marginal likelihood estimation via power posteriors and importance sampling
Li, Yong; Wang, Nianling; Yu, Jun - In: Journal of econometrics 234 (2023) 1, pp. 28-52
Persistent link: https://www.econbiz.de/10014364649
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A new approach to Bayesian hypothesis testing
Li, Yong; Zeng, Tao; Yu, Jun - In: Journal of econometrics 178 (2014) 1, pp. 602-612
Persistent link: https://www.econbiz.de/10010256849
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Time-varying sparsity in dynamic regression models
Kalli, Maria; Griffin, Jim E. - In: Journal of econometrics 178 (2014) 2, pp. 779-793
Persistent link: https://www.econbiz.de/10010257660
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A Bayesian chi-squared test for hypothesis testing
Li, Yong; Liu, Xiao-Bin; Yu, Jun - In: Journal of econometrics 189 (2015) 1, pp. 54-69
Persistent link: https://www.econbiz.de/10011502408
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Modelling regional patterns of inefficiency : a Bayesian approach to geoadditive panel stochastic frontier analysis with an application to cereal production in England and Wales
Klein, Nadja; Herwartz, Helmut; Kneib, Thomas - In: Journal of econometrics 214 (2020) 2, pp. 513-539
Persistent link: https://www.econbiz.de/10012439076
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Deviance information criterion for latent variable models and misspecified models
Li, Yong; Yu, Jun; Zeng, Tao - In: Journal of econometrics 216 (2020) 2, pp. 450-493
Persistent link: https://www.econbiz.de/10012439750