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~person:"Billio, Monica"
~person:"Lang, Stefan"
~subject:"Regressionsanalyse"
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Billio, Monica
Lang, Stefan
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14
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Bayesian structured additive distributional regression for multivariate responses
Klein, Nadja
;
Kneib, Thomas
;
Klasen, Stephan
;
Lang, Stefan
-
2013
Markov chain
Monte
Carlo algorithm based on iteratively weighted least squares approximations and with multivariate Gaussian …
Persistent link: https://www.econbiz.de/10010200433
Saved in:
2
Bayesian structured additive distributional regression
Klein, Nadja
;
Kneib, Thomas
;
Lang, Stefan
-
2013
basis function coefficients. Inference is then based on efficient Markov chain
Monte
Carlo simulation techniques where a …
Persistent link: https://www.econbiz.de/10010189552
Saved in:
3
Bayesian dynamic tensor regression
Billio, Monica
;
Casarin, Roberto
;
Iacopini, Matteo
; …
- In:
Journal of business & economic statistics : JBES ; a …
41
(
2023
)
2
,
pp. 429-439
Persistent link: https://www.econbiz.de/10014448234
Saved in:
4
Multilevel structured additive regression
Lang, Stefan
;
Umlauf, Nikolaus
;
Wechselberger, Peter
; …
-
2012
Persistent link: https://www.econbiz.de/10009571097
Saved in:
5
Multilevel structured additive regression
Lang, Stefan
;
Umlauf, Nikolaus
;
Wechselberger, Peter
; …
-
2012
Monte
Carlo simulation techniques. We provide an in depth description of several highly efficient sampling schemes that …
Persistent link: https://www.econbiz.de/10009742083
Saved in:
6
Bayesian Markov Switching Tensor Regression For Time-Varying Networks
Billio, Monica
-
2018
We propose a new Bayesian Markov switching regression model for multi-dimensional arrays (tensors) of binary time series. We assume a zero-inflated logit dynamics with time-varying parameters and apply it to multi-layer temporal networks. The original contribution is threefold. First, in order...
Persistent link: https://www.econbiz.de/10012917228
Saved in:
7
Bayesian Dynamic Tensor Regression
Billio, Monica
;
Casarin, Roberto
;
Kaufmann, Sylvia
; …
-
2018
combined with
Monte
Carlo Markov Chain (MCMC). We show the efficiency of the MCMC procedure on simulated datasets, with …
Persistent link: https://www.econbiz.de/10014113407
Saved in:
8
Bayesian Nonparametric Sparse Seemingly Unrelated Regression Model (SUR)
Billio, Monica
-
2017
Seemingly unrelated regression (SUR) models are useful in studying the interactions among different variables. In a high dimensional setting or when applied to large panel of time series, these models require a large number of parameters to be estimated and suffer of inferential problems.To...
Persistent link: https://www.econbiz.de/10012968298
Saved in:
9
Random scaling factors in Bayesian distributional regression models with an application to real estate data
Razen, Alexander
;
Lang, Stefan
-
2016
Monte
Carlo (MCMC) algorithms. We investigate the statistical properties of our approach within extensive simulation …
Persistent link: https://www.econbiz.de/10011549047
Saved in:
10
Bayesian nonparametric sparse seemingly unrelated regression model (SUR)
Billio, Monica
;
Casarin, Roberto
;
Rossini, Luca
-
2016
Persistent link: https://www.econbiz.de/10011629460
Saved in:
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