J. Gertheiss

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Sparse Modeling of Categorial Explanatory Variables

G. Tutz, J. Gertheiss, 2011, 1101.1421.

Marginal Functional Regression Models for Analyzing the Feeding Behavior of Pigs

A. Staicu, J. Gertheiss, Verena K. Maier, 2015 .

Penalized Regression with Ordinal Predictors

G. Tutz, J. Gertheiss, 2009 .

Activation of the NF-κB pathway alters the phenotype of MSCs in the tracheal aspirates of preterm infants with severe BPD.

S. Bellusci, R. Morty, A. Schulze, 2018, American journal of physiology. Lung cellular and molecular physiology.

Spatially regularized estimation for the analysis of dynamic contrast‐enhanced magnetic resonance imaging data

Jan Gertheiss, Volker J Schmid, Julia C. Sommer, 2014, Statistics in medicine.

ANOVA for Factors With Ordered Levels

J. Gertheiss, 2014 .

A Flexible Link Function for Discrete-Time Duration Models

G. Tutz, J. Gertheiss, W. Hess, 2016 .

Boosting in Nonlinear Regression Models with an Application to DCE-MRI Data

Volker J Schmid, J Gertheiss, B. Bischl, 2015, Methods of Information in Medicine.

Selection of ordinally scaled independent variables with applications to international classification of functioning core sets

Gerhard Tutz, Jan Gertheiss, G. Tutz, 2011 .

Selection of Ordinally Scaled Independent Variables

G. Tutz, J. Gertheiss, Sara Hogger, 2009 .

Random forests for functional covariates

G. Tutz, J. Gertheiss, A. Möller, 2016 .

Variable Selection and Weighting by Nearest Neighbor Ensembles

J. Gertheiss, 2008 .

Analysis of DCE-MRI Data using a Nonnegative Elastic Net

Volker J Schmid, J. Gertheiss, J. C. Karcher, 2010 .

Testing differentially expressed genes in dose-response studies and with ordinal phenotypes

C. Crainiceanu, E. Sweeney, J. Gertheiss, 2016, Statistical applications in genetics and molecular biology.

Validation of boar taint detection by sensory quality control: Relationship between sample size and uncertainty of performance indicators.

R. Christensen, D. Mörlein, J. Gertheiss, 2015, Meat science.

Penalized Optimal Scaling for Ordinal Variables with an Application to International Classification of Functioning Core Sets

H. Kiers, J. Gertheiss, Aisouda Hoshiyar, 2021, 2110.02805.

Nonparametric regression and classification with functional, categorical, and mixed covariates

J. Gertheiss, Leonie Selk, 2021, Advances in Data Analysis and Classification.

Sustainable use of tainted boar meat: Blending is a strategy for processed products.

D. Mörlein, L. Meier-Dinkel, J. Gertheiss, 2019, Meat science.

Spatially regularized estimation for the analysis of DCE-MRI data

Volker J Schmid, Julia C. Sommer, J. Gertheiss, 2012 .

Rating Scales as Predictors—The Old Question of Scale Level and Some Answers

G. Tutz, J. Gertheiss, 2013, Psychometrika.

A modification of McFadden's R2 for binary and ordinal response models

J. Gertheiss, E. Ugba, 2022, Communications for Statistical Applications and Methods.

Regularized regression for categorical data

Gerhard Tutz, Jan Gertheiss, G. Tutz, 2016 .

Discussion of “The Evolution of Boosting Algorithms” and “Extending Statistical Boosting”

A Ziegler, Z Wang, J Gertheiss, 2014, Methods of Information in Medicine.

Feature Extraction in Signal Regression: A Boosting Technique for Functional Data Regression

Gerhard Tutz, Jan Gertheiss, G. Tutz, 2010 .

Human perception of color differences using computer vision system measurements of raw pork loin.

I. Tomašević, D. Mörlein, J. Gertheiss, 2022, Meat science.

Variable selection in generalized functional linear models

J Gertheiss, A Maity, A-M Staicu, 2013, Stat.

How olfactory acuity affects the sensory assessment of boar fat: a proposal for quantification.

Daniel Mörlein, Jan Gertheiss, Michael Wicke, 2014, Meat science.

Statistical inference for ordinal predictors in generalized additive models with application to Bronchopulmonary Dysplasia

Fabian Scheipl, Jan Gertheiss, Tina Lauer, 2021, BMC research notes.

Nearest neighbor ensembles for functional data with interpretable feature selection

Gerhard Tutz, Jan Gertheiss, Karen Fuchs, 2015 .

Interaction of Skatole and Androstenone in the Olfactory Perception of Boar Taint.

C. Looft, E. Tholen, D. Mörlein, 2016, Journal of agricultural and food chemistry.

Boar taint detection: A comparison of three sensory protocols.

Daniel Mörlein, Jan Gertheiss, Lisa Meier-Dinkel, 2016, Meat science.

Evaluating the performance of sensory quality control: the case of boar taint.

Daniel Mörlein, Jan Gertheiss, Lisa Meier-Dinkel, 2015, Meat science.

Feature Selection and Weighting by Nearest Neighbor Ensembles

Gerhard Tutz, Jan Gertheiss, G. Tutz, 2009 .

Smoothing in Ordinal Regression: An Application to Sensory Data

Daniel Mörlein, Jan Gertheiss, Ejike R. Ugba, 2021, Stats.

Bacterial Colonization within the First Six Weeks of Life and Pulmonary Outcome in Preterm Infants <1000 g

M. Schloter, T. Chakraborty, J. Gertheiss, 2020, Journal of clinical medicine.

Supervised learning for analysing movement patterns in a virtual reality experiment

M. Tomasik, J. Gertheiss, N. Vahle, 2022, Royal Society Open Science.

Using Lasso-Type Penalties to Model Time-Varying Covariate Effects in Panel Data Regressions – A Novel Approach Illustrated by the 'Death of Distance' In International Trade

M. Persson, J. Gertheiss, W. Hess, 2013 .

Having the Second Leg at Home - Advantage in the UEFA Champions League Knockout Phase?

Manuel J. A. Eugster, Jan Gertheiss, M. Eugster, 2011 .

Engineering Human-Machine Teams for Trusted Collaboration

Michael Prilla, Jörg P. Müller, Rüdiger Ehlers, 2020, Big Data Cogn. Comput..

Generalized Functional Additive Mixed Models

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

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

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

Regression and Alignment for Functional Data and Network Topology

R. Gur, R. Gur, T. Satterthwaite, 2023, bioRxiv.

Rating Scales as Predictors—The Old Question of Scale Level and Some Answers

Gerhard Tutz, Jan Gertheiss, G. Tutz, 2013, Psychometrika.

Penalized optimal scaling for ordinal variables with an application to international classification of functioning core sets.

H. Kiers, J. Gertheiss, Aisouda Hoshiyar, 2021, The British journal of mathematical and statistical psychology.

Penalized Non-Linear Principal Components Analysis for Ordinal Variables with an Application to International Classification of Functioning Core Sets

Jan Gertheiss, Henk A.L. Kiers, Aisouda Hoshiyar, 2021 .

Marginal Functional Regression Models for Analyzing the Feeding Behavior of Pigs

A. Staicu, J. Gertheiss, Verena K. Maier, 2015, Journal of Agricultural, Biological, and Environmental Statistics.

Regularization and model selection with categorical predictors and effect modifiers in generalized linear models

Gerhard Tutz, Jan Gertheiss, Margret-Ruth Oelker, 2014 .

Regularization and Model Selection with Categorial Effect Modifiers

Gerhard Tutz, Jan Gertheiss, G. Tutz, 2010 .

A note on modeling sparse exponential-family functional response curves

Ana-Maria Staicu, Jeff Goldsmith, Jan Gertheiss, 2017, Comput. Stat. Data Anal..

Regularization and Model Selection for Item-on-Items Regression with Applications to Food Products' Survey Data

J. Gertheiss, Aisouda Hoshiyar, Laura H. Gertheiss, 2023, 2309.16373.

Consumers' perception and acceptance of boiled and fermented sausages from strongly boar tainted meat.

D. Mörlein, L. Meier-Dinkel, J. Gertheiss, 2016, Meat science.

Testing linearity and relevance of ordinal predictors

Jan Gertheiss, J. Gertheiss, Franziska Oehrlein, 2011 .

Rejoinder: Regularized regression for categorical data

G. Tutz, J. Gertheiss, 2016 .

Regularization and Model Selection with Categorical Covariates

Gerhard Tutz, Jan Gertheiss, Veronika Stelz, 2013, Algorithms from and for Nature and Life.

Feature Extraction in Regression and Classification with Structured Predictors

J. Gertheiss, 2022 .