4 papers · 1 filter
Gradient-Boosted Generalized Linear Models for Conditional Vine Copulas
David Jobst, Annette Möller, Jürgen Groß
Vine copulas are flexible dependence models using bivariate copulas as building blocks. If the parameters of the bivariate copulas in the vine copula depend on covariates, one obta…
D-Vine GAM Copula based Quantile Regression with Application to Ensemble Postprocessing
David Jobst, Annette Möller, Jürgen Groß
Temporal, spatial or spatio-temporal probabilistic models are frequently used for weather forecasting. The D-vine (drawable vine) copula quantile regression (DVQR) is a powerful to…
Some Additional Remarks on Statistical Properties of Cohen's d from Linear Regression
Jürgen Groß, Annette Möller
The size of the effect of the difference in two groups with respect to a variable of interest may be estimated by the classical Cohen's . A recently proposed generalized estimat…
Effect Size Estimation in Linear Mixed Models
Jürgen Groß, Annette Möller
In this note, we reconsider Cohen's effect size measure under linear mixed models and demonstrate its application by employing an artificially generated data set. It is shown…