Sonja Greven

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Boosting flexible functional regression models with a high number of functional historical effects

Friedrich Leisch, Michael Melcher, Sarah Brockhaus, 2016, Statistics and Computing.

Longitudinal scalar-on-functions regression with application to tractography data.

Ciprian Crainiceanu, Jeff Goldsmith, Jan Gertheiss, 2013, Biostatistics.

Selective inference after likelihood- or test-based model selection in linear models

Sonja Greven, David Rugamer, S. Greven, 2017, Statistics & Probability Letters.

The impact of model assumptions in scalar‐on‐image regression

Sonja Greven, Clara Happ, Volker J Schmid, 2017, Statistics in medicine.

Functional Additive Mixed Models

Ana-Maria Staicu, Fabian Scheipl, Sonja Greven, 2012, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.

Nonlinear association structures in flexible Bayesian additive joint models

Nikolaus Umlauf, Sonja Greven, Meike Köhler, 2017, Statistics in medicine.

Longitudinal High-Dimensional Principal Components Analysis with Application to Diffusion Tensor Imaging of Multiple Sclerosis.

Brian Caffo, Vadim Zipunnikov, Haochang Shou, 2015, The annals of applied statistics.

Valid Inference for L 2 -Boosting.

Sonja Greven, David Rügamer, S. Greven, 2018 .

Boosting factor‐specific functional historical models for the detection of synchronization in bioelectrical signals

Sarah Brockhaus, Sonja Greven, David Rugamer, 2016, 1609.06070.

Inference for $$L_2$$L2-Boosting

Sonja Greven, David Rügamer, S. Greven, 2020, Stat. Comput..

Identifiability in penalized function-on-function regression models

Fabian Scheipl, Sonja Greven, S. Greven, 2015, 1506.03627.

Generalized Functional Additive Mixed Models

Fabian Scheipl, Jan Gertheiss, Sonja Greven, 2015, 1506.05384.

Penalized scalar-on-functions regression with interaction term

Karen Fuchs, Fabian Scheipl, Sonja Greven, 2015, Comput. Stat. Data Anal..

Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models

Helmut Küchenhoff, Fabian Scheipl, Sonja Greven, 2008, Comput. Stat. Data Anal..

Selective Inference for $L_2$-Boosting

Sonja Greven, David Rugamer, S. Greven, 2018, 1805.01852.

Mixed modeling for irregularly sampled and correlated functional data: Speech science applications.

Philip Hoole, Sonja Greven, Marianne Pouplier, 2017, The Journal of the Acoustical Society of America.

Flexible Bayesian additive joint models with an application to type 1 diabetes research

Nikolaus Umlauf, Sonja Greven, Christiane Winkler, 2016, Biometrical journal. Biometrische Zeitschrift.

Longitudinal functional principal component analysis.

Brian Caffo, Ciprian Crainiceanu, Sonja Greven, 2010, Electronic journal of statistics.

Structured functional principal component analysis

Ciprian M Crainiceanu, Vadim Zipunnikov, Haochang Shou, 2013, Biometrics.

Fast symmetric additive covariance smoothing

Fabian Scheipl, Sonja Greven, Jona Cederbaum, 2016, Comput. Stat. Data Anal..

Conditional Model Selection in Mixed-Effects Models with cAIC4

Thomas Kneib, Sonja Greven, David Rugamer, 2018, J. Stat. Softw..

Valid Inference for L2-Boosting pdf

Sonja Greven, David Rügamer, 2018, ArXiv.

Elastic analysis of irregularly or sparsely sampled curves

Sonja Greven, Lisa Steyer, Almond Stocker, 2021 .

Navigating the corporate disclosure gap: Modelling of Missing Not at Random Carbon Data

Sonja Greven, Jaakko Kooroshy, Malgorzata Olesiewicz, 2021, 2112.07784.

Predicting Question Difficulty in Web Surveys: A Machine Learning Approach Based on Mouse Movement Features

Frauke Kreuter, Felix Henninger, Pascal J. Kieslich, 2021, Social Science Computer Review.

Generalised functional additive mixed models with compositional covariates for areal Covid-19 incidence curves (preprint)/ en

Jorge Mateu, Matthias Eckardt, Sonja Greven, 2022, 2201.08362.

Additive Density-on-Scalar Regression in Bayes Hilbert Spaces with an Application to Gender Economics

Sonja Greven, Bernd Fitzenberger, Almond Stocker, 2021 .

Functional additive models on manifolds of planar shapes and forms

Sonja Greven, Almond Stocker, 2021 .

Multivariate functional additive mixed models

Fabian Scheipl, Sonja Greven, Almond Stocker, 2021, Statistical Modelling.

Selective inference for additive and linear mixed models

Sonja Greven, David Rügamer, Philipp F. M. Baumann, 2020, Comput. Stat. Data Anal..

Functional linear mixed models for irregularly or sparsely sampled data

Phil Hoole, Sonja Greven, Marianne Pouplier, 2015, 1508.01686.

An Approach to the Estimation of Chronic Air Pollution Effects Using Spatio-Temporal Information

Francesca Dominici, Sonja Greven, Scott Zeger, 2011, Journal of the American Statistical Association.

Signal regression models for location, scale and shape with an application to stock returns

Sarah Brockhaus, Sonja Greven, Andreas Fuest, 2016, 1605.04281.

A general framework for functional regression modelling

Fabian Scheipl, Sonja Greven, S. Greven, 2017 .

LONGITUDINAL HIGH-DIMENSIONAL DATA ANALYSIS

Brian S. Caffo, Daniel S. Reich, Vadim Zipunnikov, 2011 .

The functional linear array model

Torsten Hothorn, Fabian Scheipl, Sarah Brockhaus, 2015 .