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Bayesian analysis of econometric time series models using hybrid integration rules
Moreira, Ajax; Gamerman, Dani - 2015
This paper is concerned with the study of Bayesian inference procedures to commonly used time series models. In … are analytically integrated and hyperparameters are integrated by Markov chain Monte Carlo methods. Credibility regions …
Persistent link: https://www.econbiz.de/10012018632
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Multivariate spatial regression models
Gamerman, Dani; Moreira, Ajax - 2015
This paper describes the inference procedures required to perform Bayesian inference to some multivariate econometric …
Persistent link: https://www.econbiz.de/10012019328
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Bayesian analysis of econometric time series models using hybrid integration rules
Moreira, Ajax; Gamerman, Dani - 2001
This paper is concerned with the study of Bayesian inference procedures to commonly used time series models. In … are analytically integrated and hyperparameters are integrated by Markov chain Monte Carlo methods. Credibility regions …
Persistent link: https://www.econbiz.de/10011762920
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Bayesian analysis of econometric time series models using hybrid integration rules
Moreira, Ajax Reynaldo Bello; Gamerman, Dani - 2015
This paper is concerned with the study of Bayesian inference procedures to commonly used time series models. In … are analytically integrated and hyperparameters are integrated by Markov chain Monte Carlo methods. Credibility regions …
Persistent link: https://www.econbiz.de/10012234118
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Space-varying regression models: Specifications and simulation
Gamerman, Dani; Moreira, Ajax Reynaldo Bello; Rue, Håvard - 2015
Space-varying regression models are generalizations of standard linear models where the regression coefficients are allowed to change in space. The spatial structure is specified by a multivariate extension of pairwise difference priors thus enabling incorporation of neighboring structures and...
Persistent link: https://www.econbiz.de/10012234115
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Space-varying regression models : specifications and simulation
Gamerman, Dani; Moreira, Ajax; Rue, Håvard - 2015
Space-varying regression models are generalizations of standard linear models where the regression coefficients are allowed to change in space. The spatial structure is specified by a multivariate extension of pairwise difference priors thus enabling incorporation of neighboring structures and...
Persistent link: https://www.econbiz.de/10012007896
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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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Bayesian estimation of the GARCH(1,1) model with student-t innovations
Ardia, David; Hoogerheide, Lennart F. - 2010
This note presents the R package bayesGARCH (Ardia, 2007) which provides functions for the Bayesian estimation of the …
Persistent link: https://www.econbiz.de/10011380176
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Markov chain Monte Carlo in Bayesian models for testing gamma and lognormal S-type process qualities
Liao, Mou-Yuan - In: International journal of production research 54 (2016) 23/24, pp. 7491-7503
Persistent link: https://www.econbiz.de/10011566617
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Space-varying regression models : specifications and simulation
Gamerman, Dani; Moreira, Ajax; Rue, Håvard - 2001
Space-varying regression models are generalizations of standard linear models where the regression coefficients are allowed to change in space. The spatial structure is specified by a multivariate extension of pairwise difference priors, thus enabling incorporation of neighboring structures and...
Persistent link: https://www.econbiz.de/10011773664