Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models. - Fabian Scheipl; Sonja Greven; Helmut Küchenhoff (Comput. Stat. Data Anal., 2008)

Penalized scalar-on-functions regression with interaction term. - Karen Fuchs; Fabian Scheipl; Sonja Greven (Comput. Stat. Data Anal., 2015)

Penalized function-on-function regression. - Andrada E. Ivanescu; Ana-Maria Staicu; Fabian Scheipl; Sonja Greven (Comput. Stat., 2015)

Boosting flexible functional regression models with a high number of functional historical effects. - Sarah Brockhaus; Michael Melcher; Friedrich Leisch; Sonja Greven (Stat. Comput., 2017)

Valid Inference for L2-Boosting. - David Rügamer; Sonja Greven (CoRR, 2018)

Fast symmetric additive covariance smoothing. - Jona Cederbaum; Fabian Scheipl; Sonja Greven (Comput. Stat. Data Anal., 2018)

Predicting respondent difficulty in web surveys: A machine-learning approach based on mouse movement features. - Amanda Fernández-Fontelo; Pascal J. Kieslich; Felix Henninger; Frauke Kreuter; Sonja Greven (CoRR, 2020)

Inference for L2-Boosting. - David Rügamer; Sonja Greven (Stat. Comput., 2020)

Conditional Model Selection in Mixed-Effects Models with cAIC4. - Benjamin Säfken; David Rügamer; Thomas Kneib; Sonja Greven (J. Stat. Softw., 2021)

Selective inference for additive and linear mixed models. - David Rügamer; Philipp F. M. Baumann; Sonja Greven (Comput. Stat. Data Anal., 2022)

Adaptive step-length selection in gradient boosting for Gaussian location and scale models. - Boyao Zhang; Tobias Hepp 001; Sonja Greven; Elisabeth Bergherr (Comput. Stat., 2022)

Functional Additive Models on Manifolds of Planar Shapes and Forms. - Almond Stöcker; Lisa Steyer; Sonja Greven (J. Comput. Graph. Stat., 2023)

Deep Nonparametric Conditional Independence Tests for Images. - Marco Simnacher; Xiangnan Xu; Hani Park; Christoph Lippert; Sonja Greven (CoRR, 2024)