96 citations · 128 across the 8 of their papers we have counts for
6 papers · 1 filter
Nonparametric Estimation of the Underlying Distribution of Binned Continuous Data
Ejike R. Ugba, Jan Gertheiss
The estimation of cumulative distribution functions (CDF) and probability density functions (PDF) is a fundamental practice in applied statistics. However, challenges often arise w…
Regularization and Model Selection for Ordinal-on-Ordinal Regression with Applications to Food Products' Testing and Survey Data
Aisouda Hoshiyar, Laura H. Gertheiss, Jan Gertheiss
Ordinal data are quite common in applied statistics. Although some model selection and regularization techniques for categorical predictors and ordinal response models have been de…
A Modification of McFadden's for Binary and Ordinal Response Models
Ejike R. Ugba, Jan Gertheiss
A lot of studies on the summary measures of predictive strength of categorical response models consider the likelihood ratio index (LRI), also known as the McFadden-, a better…
Nonparametric Regression and Classification with Functional, Categorical, and Mixed Covariates
Leonie Selk, Jan Gertheiss
We consider nonparametric prediction with multiple covariates, in particular categorical or functional predictors, or a mixture of both. The method proposed bases on an extension o…
Statistical Inference for Ordinal Predictors in Generalized Linear and Additive Models with Application to Bronchopulmonary Dysplasia
Jan Gertheiss, Fabian Scheipl, Tina Lauer +1
Discrete but ordered covariates are quite common in applied statistics, and some regularized fitting procedures have been proposed for proper handling of ordinal predictors in stat…
Generalized Functional Additive Mixed Models
Fabian Scheipl, Jan Gertheiss, Sonja Greven
We propose a comprehensive framework for additive regression models for non-Gaussian functional responses, allowing for multiple (partially) nested or crossed functional random eff…