Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Perrakis, Konstantinos"'
We introduce a novel class of Bayesian mixtures for normal linear regression models which incorporates a further Gaussian random component for the distribution of the predictor variables. The proposed cluster-weighted model aims to encompass potentia
Externí odkaz:
http://arxiv.org/abs/2411.18957
In this paper we present Poisson mixture approaches for origin-destination (OD) modeling in transportation analysis. We introduce covariate-based models which incorporate different transport modeling phases and also allow for direct probabilistic inf
Externí odkaz:
http://arxiv.org/abs/2011.06045
Regularized regression models are well studied and, under appropriate conditions, offer fast and statistically interpretable results. However, large data in many applications are heterogeneous in the sense of harboring distributional differences betw
Externí odkaz:
http://arxiv.org/abs/1908.07869
Applications of high-dimensional regression often involve multiple sources or types of covariates. We propose methodology for this setting, emphasizing the "wide data" regime with large total dimensionality p and sample size n<
Externí odkaz:
http://arxiv.org/abs/1710.00596
Publikováno v:
Computational Statistics and Data Analysis Volume 143, March 2020, 106836
The power-expected-posterior (PEP) prior is an objective prior for Gaussian linear models, which leads to consistent model selection inference, under the M-closed scenario, and tends to favor parsimonious models. Recently, two new forms of the PEP pr
Externí odkaz:
http://arxiv.org/abs/1609.06926
The power-expected-posterior (PEP) prior provides an objective, automatic, consistent and parsimonious model selection procedure. At the same time it resolves the conceptual and computational problems due to the use of imaginary data. Namely, (i) it
Externí odkaz:
http://arxiv.org/abs/1508.00793
Publikováno v:
In Computational Statistics and Data Analysis March 2020 143
Autor:
Warnat-Herresthal, Stefanie, Perrakis, Konstantinos, Taschler, Bernd, Becker, Matthias, Baßler, Kevin, Beyer, Marc, Günther, Patrick, Schulte-Schrepping, Jonas, Seep, Lea, Klee, Kathrin, Ulas, Thomas, Haferlach, Torsten, Mukherjee, Sach, Schultze, Joachim L.
Publikováno v:
In iScience 24 January 2020 23(1)
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Aircraft Engineering and Aerospace Technology: An International Journal, 2016, Vol. 88, Issue 2, pp. 285-293.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/AEAT-02-2015-0071