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Enhanced variable selection for boosting sparser and less complex models in distributional copula regression

Autor: Strömer, Annika, Klein, Nadja, Staerk, Christian, Faschingbauer, Florian, Klinkhammer, Hannah, Mayr, Andreas

Structured additive distributional copula regression allows to model the joint distribution of multivariate outcomes by relating all distribution parameters to covariates. Estimation via statistical boosting enables accounting for high-dimensional da

Externí odkaz: http://arxiv.org/abs/2406.03900

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Boosting Distributional Copula Regression for Bivariate Binary, Discrete and Mixed Responses

Autor: Sanchez, Guillermo Briseño, Klein, Nadja, Klinkhammer, Hannah, Mayr, Andreas

Motivated by challenges in the analysis of biomedical data and observational studies, we develop statistical boosting for the general class of bivariate distributional copula regression with arbitrary marginal distributions, which is suited to model

Externí odkaz: http://arxiv.org/abs/2403.02194

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