3 papers
stat.ME2024
Prediction modelling with many correlated and zero-inflated predictors: assessing a nonnegative garrote approach
Mariella Gregorich, Michael Kammer, Harald Mischak +1
Building prediction models from mass-spectrometry data is challenging due to the abundance of correlated features with varying degrees of zero-inflation, leading to a common intere…
stat.ME2023
Flexible parametrization of graph-theoretical features from individual-specific networks for prediction
Mariella Gregorich, Sean L. Simpson, Georg Heinze
Statistical techniques are needed to analyse data structures with complex dependencies such that clinically useful information can be extracted. Individual-specific networks, which…
stat.ME2023
Fractional Polynomials Models as Special Cases of Bayesian Generalized Nonlinear Models
Aliaksandr Hubin, Georg Heinze, Riccardo De Bin
We propose a framework for fitting fractional polynomials models as special cases of Bayesian Generalized Nonlinear Models, applying an adapted version of the Genetically Modified…