5 papers · 1 filter
Reconciling Interpretability with Covariate-Dependent Shape Flexibility in Penalized Transformation Models for Distributional Regression
Johannes Brachem, Thomas Kneib
A central challenge in distributional regression is to allow the shape of the conditional distribution of the response variable to vary flexibly with covariates while retaining dir…
Bayesian structured additive quantile regression for inflated bounded data
Francisco F. Queiroz, Johannes Brachem, Paul F. V. Wiemann +1
Bounded continuous data on the unit interval frequently arise in applied fields and often exhibit a non-negligible proportion of observations at the boundaries. Inflated regression…
Graphical Transformation Models
Matthias Herp, Johannes Brachem, Michael Altenbuchinger +1
Graphical Transformation Models (GTMs) are introduced as a novel approach to effectively model multivariate data with intricate marginals and complex dependency structures semipara…
Bayesian Penalized Transformation Models: Structured Additive Location-Scale Regression for Arbitrary Conditional Distributions
Johannes Brachem, Paul F. V. Wiemann, Thomas Kneib
Penalized transformation models (PTMs) are a semiparametric location-scale regression family that estimate a response's conditional distribution directly from the data, and model t…
A simplified spatial+ approach to mitigate spatial confounding in multivariate spatial areal models
A. Urdangarin, T. Goicoa, T. Kneib +1
Spatial areal models encounter the well-known and challenging problem of spatial confounding. This issue makes it arduous to distinguish between the impacts of observed covariates…