1 citations · 2 across the 7 of their papers we have counts for
7 papers
Bayesian Effect Selection for Additive Quantile Regression with an Application to Air Pollution Thresholds
Nadja Klein, Aaron Wei Qi Lee, Jorge Mateu
Air pollution regulatory limits are typically defined in terms of exceedances of concentration thresholds which are naturally related to conditional quantiles of the pollutant dist…
Semi-structured multi-state delinquency model for mortgage default
Victor Medina-Olivares, Wangzhen Xia, Stefan Lessmann +1
We propose a semi-structured discrete-time multi-state model to analyse mortgage delinquency transitions. This model combines an easy-to-understand structured additive predictor, w…
Scalable Learning of Multivariate Distributions via Coresets
Zeyu Ding, Katja Ickstadt, Nadja Klein +2
Efficient and scalable non-parametric or semi-parametric regression analysis and density estimation are of crucial importance to the fields of statistics and machine learning. Howe…
Boosting Distributional Copula Regression for Bivariate Right-Censored Time-to-Event Data
Guillermo Briseno-Sanchez, Nadja Klein, Andreas Groll +1
We propose a highly flexible distributional copula regression model for bivariate time-to-event data in the presence of right-censoring. The joint survival function of the response…
Enhanced variable selection for boosting sparser and less complex models in distributional copula regression
Annika Strömer, Nadja Klein, Christian Staerk +3
Structured additive distributional copula regression allows to model the joint distribution of multivariate outcomes by relating all distribution parameters to covariates. Estimati…
Boosting Distributional Copula Regression for Bivariate Binary, Discrete and Mixed Responses
Guillermo Briseño Sanchez, Nadja Klein, Hannah Klinkhammer +1
Motivated by challenges in the analysis of biomedical data and observational studies, we develop statistical boosting for the general class of bivariate distributional copula regre…
Regression Copulas for Multivariate Responses
Nadja Klein, Michael Stanley Smith, David Nott +1
We propose a novel distributional regression model for a multivariate response vector based on a copula process over the covariate space. It uses the implicit copula of a Gaussian…