In this paper, we propose a unified Bayesian approach for multivariate structured additive distributional regression analysis where inference is applicable to a huge class of multivariate response distributions, comprising continuous, discrete and latent models, and where each parameter of these...

In diesem Aufsatz beschreiben wir einen neuartigen Ansatz, mit dem zwei heterogene Datensätze für räumliche Hauspreisvorhersagen nutzbar gemacht werden. Der erste Datensatz enthält eine große Anzahl von Hauspreisbeobachtungen, allerdings nur wenige Immobilieneigenschaften (ein langer...

This paper discusses random intercept selection within the context of semiparametric regression models with structured additive predictor (STAR). STAR models can deal simultaneously with nonlinear covariate effects and time trends, unit- or cluster-specific heterogeneity, spatial heterogeneity...

The Directive 2002/91/EC of the European Parliament and of the Council of 16 December 2002 (Energy Performance of Buildings Directive, EPD) requires member states to introduce an energy certification in order to reduce energy consumption in buildings. This new directive should help reveal saving...

Whereas child mortality has been decreased globally in the last 20 years, high levels persist in Sub-Saharan Africa. This paper analyzes child mortality in 25 Sub-Saharan countries based on household survey data. We employ a new multilevel approach with structured additive predictor within the...

Quantile regression provides a convenient framework for analyzing the impact of covariates on the complete conditional distribution of a response variable instead of only the mean. While frequentist treatments of quantile regression are typically completely nonparametric, a Bayesian formulation...

Models with structured additive predictor provide a very broad and rich framework for complex regression modeling. They can deal simultaneously with nonlinear covariate effects and time trends, unit- or cluster-specific heterogeneity, spatial heterogeneity and complex interactions between...

Structured additive regression (STAR) models provide a flexible framework for modeling possible nonlinear effects of covariates: They contain the well established frameworks of generalized linear models (GLM) and generalized additive models (GAM) as special cases but also allow a wider class of...

Models with structured additive predictor provide a very broad and rich framework for complex regression modeling. They can deal simultaneously with nonlinear covariate effects and time trends, unit- or cluster specific heterogeneity, spatial heterogeneity and complex interactions between...

Distributional structured additive regression provides a flexible framework for modeling each parameter of a potentially complex response distribution in dependence of covariates. Structured additive predictors allow for an additive decomposition of covariate effects with nonlinear effects and...