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Eine Ebene höher- Fakultäten (107377)
- Mathematik, Informatik und Statistik (5326)
- Statistik (2301)
- Lehrstühle/Arbeitsgruppen (742)
- Seminar für angewandte Stochastik (79)
- Lehrstühle/Arbeitsgruppen (742)
- Statistik (2301)
- Mathematik, Informatik und Statistik (5326)
Anzahl der Publikationen auf dieser Ebene: 79
A
Asgharian, Hossein; Hess, Wolfgang und Liu, Lu
(2013):
A spatial analysis of international stock market linkages.
In: Journal of Banking & Finance, Bd. 37, Nr. 12: S. 4738-4754
B
Berger, Moritz und Tutz, Gerhard
(2016):
Detection of Uniform and Nonuniform Differential Item Functioning by Item Focussed Trees.
In: Journal of Educational and Behavioral Statistics, Bd. 41, Nr. 6: S. 559-592
[PDF, 658kB]
Bühlmann, Peter; Gertheiss, Jan; Hieke, Stefanie; Kneib, Thomas; Ma, Shuangge; Schumacher, Martin; Tutz, Gerhard; Wang, Ching-Yun; Wang, Zhu und Ziegler, Andreas
(2014):
Discussion of ``The Evolution of Boosting Algorithms'' and ``Extending Statistical Boosting''.
In: Methods of Information in Medicine, Bd. 53: S. 436-445
C
Casalicchio, Giuseppe; Tutz, Gerhard und Schauberger, Gunther
(2015):
Subject-specific Bradley-Terry-Luce models with implicit variable selection.
In: Statistical Modelling, Bd. 15, Nr. 6: S. 526-547
[PDF, 249kB]
D
Draxler, Clemens; Tutz, Gerhard; Zink, Katharina und Gürer, Can
(2016):
Comparison of Maximum Likelihood with Conditional Pairwise Likelihood Estimation of Person Parameters in the Rasch Model.
In: Communications in Statistics - Simulation and Computation, Bd. 45, Nr. 6: S. 2007-2017
F
Fuchs, Karen; Gertheiss, Jan und Tutz, Gerhard
(2015):
Nearest neighbor ensembles for functional data with interpretable feature selection.
In: Chemometrics and Intelligent Laboratory Systems, Bd. 146: S. 186-197
G
Gertheiss, Jan; Hogger, Sarah; Oberhauser, Cornelia und Tutz, Gerhard
(2011):
Selection of Ordinally Scaled Independent Variables with Applications to International Classification of Functioning Core Sets.
In: Journal of the Royal Statistical Society: Series C, Bd. 60: S. 377-396
Gertheiss, Jan und Tutz, Gerhard
(2009):
Feature selection and weighting by nearest neighbor ensembles.
In: Chemometrics and Intelligent Laboratory Systems, Bd. 99: S. 30-38
Gertheiss, Jan und Tutz, Gerhard
(2009):
Penalized regression with ordinal predictors.
In: International Statistical Review, Bd. 77: S. 345-365
Gertheiss, Jan und Tutz, Gerhard
(2010):
Sparse modeling of categorial explanatory variables.
In: The Annals of Applied Statistics, Bd. 4: S. 2150-2180
Gertheiss, Jan und Tutz, Gerhard
(2009):
Supervised feature selection in mass spectrometry based proteomic profiling by blockwise boosting.
In: Bioinformatics, Bd. 25: S. 1076-1077
Gertheiss, Jan und Tutz, Gerhard
(2009):
Variable scaling and nearest neighbor methods.
In: Journal of Chemometrics, Bd. 23: S. 149-151
Gertheiss, Jan und Tutz, Gerhard
(2009):
Statistische Tests.
In: Schwaiger, Manfred und Meyer, Anton (Hrsg.):
Theorien und Methoden der Betriebswirtschaft. München: Vahlen. S. 439-454
Groll, Andreas; Schauberger, Gunther und Tutz, Gerhard
(2015):
Prediction of major international soccer tournaments based on team-specific regularized Poisson regression: An application to the FIFA World Cup 2014.
In: Journal of Quantitative Analysis of Sports, Bd. 11, Nr. 2: S. 97-115
[PDF, 2MB]
Groll, Andreas 
ORCID: https://orcid.org/0000-0002-6628-3539 und Tutz, Gerhard
(2012):
Regularization for Generalized Additive Mixed Models by Likelihood-Based Boosting.
In: Methods of Information in Medicine, Bd. 51, Nr. 2: S. 168-77
ORCID: https://orcid.org/0000-0002-6628-3539 und Tutz, Gerhard
(2012):
Regularization for Generalized Additive Mixed Models by Likelihood-Based Boosting.
In: Methods of Information in Medicine, Bd. 51, Nr. 2: S. 168-77
Groll, Andreas und Tutz, Gerhard
(2012):
Variable Selection for Generalized Linear Mixed Models by $L_1$-Penalized Estimation.
In: Statistics and Computing: S. 1-18
Groll, Andreas ORCID: https://orcid.org/0000-0002-6628-3539 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2014):
Variable selection for generalized linear mixed models by L1-penalized estimation.
In: Statistics and Computing, Bd. 24, Nr. 2: S. 137-154
ORCID: https://orcid.org/0000-0002-6628-3539 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2014):
Variable selection for generalized linear mixed models by L1-penalized estimation.
In: Statistics and Computing, Bd. 24, Nr. 2: S. 137-154
H
Heinzl, Felix und Tutz, Gerhard
(2014):
Additive mixed models with approximate Dirichlet process mixtures: the EM approach.
In: Statistics and Computing: S. 1-20
Heinzl, Felix und Tutz, Gerhard
(2013):
Clustering in linear mixed models with approximate Dirichlet process mixtures using EM algorithm.
In: Statistical Modelling, Bd. 13: S. 41-67
Heinzl, Felix und Tutz, Gerhard
(2014):
Clustering in linear-mixed models with a group fused lasso penalty.
In: Biometrical Journal, Bd. 56, Nr. 1: S. 44-68
Heinzl, Felix und Tutz, Gerhard
(2012):
Clustering in linear mixed models with Dirichlet process mixtures using EM algorithm.
27th International Workshop on Statistical Modelling, Prag, 16.-20. Juli 2012.
Komárek, Arnošt und Nagy, Stanislav (Hrsg.):
In: Proceedings of the 27st International Workshop on Statistical Modelling, Prag,
S. 153-158
Hess, Wolfgang; Schwarzkopf, Larissa; Hunger, Matthias und Holle, Rolf
(2014):
Competing-risks duration models with correlated random effects: an application to dementia patients' transition histories.
In: Statistics in Medicine, Bd. 33, Nr. 22: S. 3919-3931
Hess, Wolfgang; Tutz, Gerhard und Gertheiss, Jan
(2016):
A Flexible Link Function for Discrete-Time Duration Models.
In: Journal of Economics and Statistics, Bd. 236, Nr. 4: S. 455-481
Heurich, Marco; Möst, Lisa; Schauberger, Gunther; Reulen, Holger; Sustr, Pavel und Hothorn, Torsten
(2012):
Survival and causes of death of European Roe Deer before and after Eurasian Lynx reintroduction in the Bavarian Forest National Park.
In: European Journal of Wildlife Research, Bd. 58, Nr. 3: S. 567-578
K
Kneib, Thomas; Hothorn, Torsten und Tutz, Gerhard
(2009):
Variable Selection and Model Choice in Geoadditive Regression Models.
In: Biometrics, Bd. 65, Nr. 2: S. 626-634
L
Leitenstorfer, Florian und Tutz, Gerhard
(2011):
Estimation of Single-Index Models Based on Boosting Techniques.
In: Statistical Modelling, Bd. 11: S. 203-217
M
Mauerer, Ingrid ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(10. Dezember 2025):
An Ordinal Item Response Model for Understanding Attitudes.
In: Sociological Methods & Research [Forthcoming]
ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(10. Dezember 2025):
An Ordinal Item Response Model for Understanding Attitudes.
In: Sociological Methods & Research [Forthcoming]
Mauerer, Ingrid ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2023):
Heterogeneity in general multinomial choice models.
In: Statistical Methods & Applications, Bd. 32, Nr. 1: S. 129-148
[PDF, 370kB]
ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2023):
Heterogeneity in general multinomial choice models.
In: Statistical Methods & Applications, Bd. 32, Nr. 1: S. 129-148
[PDF, 370kB]
Mauerer, Ingrid ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2025):
Replication Data for: An Ordinal Item Response Model for Understanding Attitudes.
ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2025):
Replication Data for: An Ordinal Item Response Model for Understanding Attitudes.
Mauerer, Ingrid ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2024):
Replication Data for: Heterogeneity in General Multinomial Choice Models.
ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2024):
Replication Data for: Heterogeneity in General Multinomial Choice Models.
Mauerer, Ingrid ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2023):
Replication Data for: Vote Choices and Valence: Intercepts and Alternate Specifications.
ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2023):
Replication Data for: Vote Choices and Valence: Intercepts and Alternate Specifications.
Mauerer, Ingrid ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2024):
Vote Choices and Valence: Intercepts and Alternate Specifications.
In: Political Analysis, Bd. 32, Nr. 3: S. 361-378
[PDF, 378kB]
ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2024):
Vote Choices and Valence: Intercepts and Alternate Specifications.
In: Political Analysis, Bd. 32, Nr. 3: S. 361-378
[PDF, 378kB]
Mauerer, Ingrid ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2025):
Ordinal Item Response Theory Models for the Evaluation of Heterogeneity in Attitudes.
IWSM 2025 : 39th International Workshop on Statistical Modelling, University of Limerick, Ireland, 13.07.2025 - 18.07.2025.
O’Sullivan, David; Sweeney, James; Moghaddam, Shirin und Burke, Kevin (Hrsg.):
In: Proceedings of the 39th International Workshop on Statistical Modelling,
Limerick, Ireland: University of Limerick, Department of Mathematics & Statistics. S. 399-402
[PDF, 516kB]
ORCID: https://orcid.org/0000-0003-0596-4530 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(2025):
Ordinal Item Response Theory Models for the Evaluation of Heterogeneity in Attitudes.
IWSM 2025 : 39th International Workshop on Statistical Modelling, University of Limerick, Ireland, 13.07.2025 - 18.07.2025.
O’Sullivan, David; Sweeney, James; Moghaddam, Shirin und Burke, Kevin (Hrsg.):
In: Proceedings of the 39th International Workshop on Statistical Modelling,
Limerick, Ireland: University of Limerick, Department of Mathematics & Statistics. S. 399-402
[PDF, 516kB]
Mauerer, Ingrid; Pößnecker, Wolfgang; Thurner, Paul W. und Tutz, Gerhard
(2015):
Modeling electoral choices in multiparty systems with high-dimensional data: A regularized selection of parameters using the lasso approach.
In: Journal of Choice Modelling, Bd. 16: S. 23-42
Möller, Annette; Tutz, Gerhard und Gertheiss, Jan
(2016):
Random forests for functional covariates.
In: Journal of Chemometrics, Bd. 30, Nr. 12: S. 715-725
Möst, Susanne; Pößnecker, Wolfgang und Tutz, Gerhard
(2015):
Variable selection for discrete competing risks models.
In: Quality & Quantity: S. 1-22
O
Oelker, Magret-Ruth; Gertheiss, Jan und Tutz, Gerhard
(2014):
Regularization and model selection with categorical predictors and effect modifiers in generalized linear models.
In: Statistical Modeling, Bd. 14, Nr. 2: S. 157-177
[PDF, 454kB]
Oelker, Magret-Ruth; Pößnecker, Wolfgang und Tutz, Gerhard
(2015):
Selection and fusion of categorical predictors with L₀-type penalties.
In: Statistical Modelling, Bd. 15, Nr. 5: S. 389-410
[PDF, 504kB]
Oelker, Magret-Ruth; Sobotka, Fabian und Kneib, Thomas
(2014):
On (semiparametric) mode regression.
29th International Workshop on Statistical Modelling, Göttingen, 14.-18. Juli 2014.
Kneiba, Thomas; Sobotka, Fabian; Fahrenholz, Jan und Irmer, Henriette (Hrsg.):
In: Proceedings of the 29th International Workshop on Statistical Modelling,
S. 243-248
P
Petry, Sebastian und Tutz, Gerhard
(2012):
Shrinkage and Variable Selection by Polytopes.
In: Journal of Statistical Planning and Inference, Bd. 142: S. 48-64
R
Robinzonov, Nikolay; Tutz, Gerhard und Hothorn, Torsten
(2012):
Boosting techniques for nonlinear time series models.
In: AStA Advances in Statistical Analysis, Bd. 96, Nr. 1: S. 99-122
S
Schauberger, Gunther; Groll, Andreas und Tutz, Gerhard
(2017):
Analysis of the importance of on-field covariates in the German Bundesliga.
In: Journal of Applied Statistics: S. 1-18
Schauberger, Gunther und Tutz, Gerhard
(2017):
Subject-specific modelling of paired comparison data: A lasso-type penalty approach.
In: Statistical Modelling, Bd. 17, Nr. 3: S. 223-243
[PDF, 548kB]
Schauberger, Gunther und Tutz, Gerhard
(2016):
Detection of differential item functioning in Rasch models by boosting techniques.
In: British Journal of Mathematical and Statistical Psychology, Bd. 69, Nr. 1: S. 80-103
Schauberger, Gunther und Tutz, Gerhard
(2015):
Regularization Methods in Economic Forecasting.
In: Berana, Jan; Feng, Yuanhua und Hebbel, Hartmut (Hrsg.):
Empirical Economic and Financial Research. Heidelberg: Springer International Publishing. S. 61-80
Schauberger, Gunther und Tutz, Gerhard
(2012):
Effect Stars for Categorical Response Models.
27th International Workshop on Statistical Modelling, Prag, 16.-20. Juli 2012.
Komárek, Arnošt und Nagy, Stanislav (Hrsg.):
In: Proceedings of the 27st International Workshop on Statistical Modelling, Prag,
Schmid, Matthias; Küchenhoff, Helmut ORCID: https://orcid.org/0000-0002-6372-2487; Hoerauf, Achim und Tutz, Gerhard
(2016):
A survival tree method for the analysis of discrete event times in clinical and epidemiological studies.
In: Statistics in Medicine, Bd. 35, Nr. 5: S. 734-751
ORCID: https://orcid.org/0000-0002-6372-2487; Hoerauf, Achim und Tutz, Gerhard
(2016):
A survival tree method for the analysis of discrete event times in clinical and epidemiological studies.
In: Statistics in Medicine, Bd. 35, Nr. 5: S. 734-751
Shafik, Nivien und Tutz, Gerhard
(2009):
Boosting nonlinear additive autoregressive time series.
In: Computational Statistics & Data Analysis, Bd. 53: S. 2453-2464
Slawski, Martin; Castell, Wolfgang zu und Tutz, Gerhard
(2010):
Feature Selection Guided by Structural Information.
In: Annals of Applied Statistics, Bd. 4, Nr. 2: S. 1056-1080
Spiess, Martin und Tutz, Gerhard
(2010):
Logistische Regressionsverfahren für mehrkategoriale Zielvariablen.
In: Schmitz, Bernhard und Holling, Heinz (Hrsg.):
Handbuch der psychologischen Methoden und Evaluation. Göttingen: Hogrefe Verlag. S. 509-517
T
Tutz, Gerhard
(2010):
Editorial: Regularisation methods in regression and classification.
In: Statistics and Computing, Bd. 20: S. 117-118
Tutz, Gerhard
(2010):
Regression für Zählvariablen.
In: Best, Henning und Wolf, Christof (Hrsg.):
Handbuch der sozialwissenschaftlichen Datenanalyse. München: Vahlen Verlag. S. 859-876
Tutz, Gerhard
(2011):
Poisson Regression.
In: Lovric, Miodrag (Hrsg.):
International Encyclopedia of Statistical Sciences. Berlin: Springer. S. 1075-1077
Tutz, Gerhard und Gertheiss, Jan
(2010):
Feature extraction in signal regression: A boosting technique for functional data regression.
In: Journal of Computational and Graphical Statistics, Bd. 19: S. 154-174
Tutz, Gerhard und Gertheiss, Jan
(2014):
Rating Scales as Predictors - The Old Question of Scale Level and Some Answers.
In: Psychometrika, Bd. 79, Nr. 3: S. 357-376
Tutz, Gerhard und Gertheiss, Jan
(2013):
Rating Scales as Predictors - the Old Question of Scale Level and some Answers.
In: Psychometrika: S. 1-20
Tutz, Gerhard und Gertheiss, Jan
(2016):
Regularized Regression for Categorical Data.
In: Statistical Modelling, Bd. 16, Nr. 3: S. 161-200
[PDF, 832kB]
Tutz, Gerhard und Gertheiss, Jan
(2016):
Rejoinder: Regularized Regression for Categorical Data.
In: Statistical Modelling, Bd. 16, Nr. 3: S. 249-260
[PDF, 273kB]
Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539 und Groll, Andreas ORCID: https://orcid.org/0000-0002-6628-3539
(2013):
Likelihood-Based Boosting in Binary and Ordinal Random Effects Models.
In: Journal of Computational and Graphical Statistics, Bd. 22, Nr. 2: S. 356-378
ORCID: https://orcid.org/0000-0002-6628-3539 und Groll, Andreas ORCID: https://orcid.org/0000-0002-6628-3539
(2013):
Likelihood-Based Boosting in Binary and Ordinal Random Effects Models.
In: Journal of Computational and Graphical Statistics, Bd. 22, Nr. 2: S. 356-378
Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539 und Groll, Andreas
(2010):
Generalized linear mixed models based on boosting.
In: Kneib, Thomas (Hrsg.):
Statistical Modelling and Regression Structures - Festschrift in Honour of Ludwig Fahrmeir. Heidelberg: Physica-Verlag, Springer. S. 197-215
ORCID: https://orcid.org/0000-0002-6628-3539 und Groll, Andreas
(2010):
Generalized linear mixed models based on boosting.
In: Kneib, Thomas (Hrsg.):
Statistical Modelling and Regression Structures - Festschrift in Honour of Ludwig Fahrmeir. Heidelberg: Physica-Verlag, Springer. S. 197-215
Tutz, Gerhard und Koch, Dominik
(2016):
Improved nearest neighbor classifiers by weighting and selection of predictors.
In: Statistics and Computing, Bd. 26, Nr. 5: S. 1039-1057
Tutz, Gerhard und Koch, Dominik
(2016):
Improved nearest neighbor classifiers by weighting and selection of predictors.
In: Statistics and Computing, Bd. 26, Nr. 5: S. 1039-1057
Tutz, Gerhard und Oelker, Magret-Ruth
(2013):
Modeling heterogeneity by fixed effects models.
28th International Workshop on Statistical Modelling, Palermo, 8.-12. Juli 2013.
Muggeo, Vito M. R.; Capursi, Vincenza; Boscaino, Giovanni und Lovison, Gianfranco (Hrsg.):
In: Proceedings of the 28th International Workshop on Statistical Modelling,
S. 807-811
Tutz, Gerhard und Petry, Sebastian
(2016):
Generalized Additive Models with Unknown Link Function Including Variable Selection.
In: Journal of Applied Statistics, Bd. 43, Nr. 15: S. 2866-2885
Tutz, Gerhard und Petry, Sebastian
(2012):
Nonparametric Estimation of the Link Function Including Variable Selection.
In: Statistics and Computing, Bd. 21: S. 545-561
Tutz, Gerhard und Pößnecker, Wolfgang
(2012):
Variable Selection for the Multinomial Logit Model.
27th International Workshop on Statistical Modelling, Prag, 16.-20. Juli 2012.
Komárek, Arnošt und Nagy, Stanislav (Hrsg.):
In: Proceedings of the 27st International Workshop on Statistical Modelling, Prag,
S. 339-344
Tutz, Gerhard; Pößnecker, Wolfgang und Uhlmann, Lorenz
(2015):
Variable selection in general multinomial logit models.
In: Computational Statistics and Data Analysis, Bd. 82: S. 207-222
Tutz, Gerhard und Ramzan, Shalah
(2015):
Improved methods for the imputation of missing data by nearest neighbor methods.
In: Computational Statistics and Data Analysis, Bd. 90: S. 84-99
Tutz, Gerhard und Schauberger, Gunther
(2015):
A Penalty Approach to Differential Item Functioning in Rasch Models.
In: Psychometrika, Bd. 80, Nr. 1: S. 21-43
Tutz, Gerhard und Schauberger, Gunther
(2015):
A Penalty Approach to Differential Item Functioning in Rasch Models.
In: Psychometrika, Bd. 80, Nr. 1: S. 21-43
Tutz, Gerhard und Schauberger, Gunther
(2015):
Extended ordered paired comparison models with application to football data from German Bundesliga.
In: Advances in Statistical Analysis, Bd. 99, Nr. 2: S. 209-227
Tutz, Gerhard und Schauberger, Gunther
(2015):
Extended ordered paired comparison models with application to football data from German Bundesliga.
In: AStA Advances in Statistical Analysis, Bd. 99, Nr. 2: S. 209-227
Tutz, Gerhard und Schauberger, Gunther
(2013):
Visualization of Categorical Response Models - from Data Glyphs to Parameter Glyphs.
In: Journal of Computational and Graphical Statistics, Bd. 22, Nr. 1: S. 156-177
Tutz, Gerhard; Schauberger, Gunther und Berger, Moritz
(2018):
Response Styles in the Partial Credit Model.
In: Applied Psychological Measurement
[PDF, 1MB]
Tutz, Gerhard und Ulbricht, Jan
(2009):
Penalized regression with correlation based penalty.
In: Statistics and Computing, Bd. 19: S. 239-253
Z
Zahid, Faisal M. und Tutz, Gerhard
(2013):
Multinomial Logit Models with Implicit Variable Selection.
In: Advances in Data Analysis and Classification, Bd. 7, Nr. 4: S. 393-416
Zahid, Faisal M. und Tutz, Gerhard
(2013):
Ridge Estimation for Multinomial Logit Models with Symmetric Side Constraints.
In: Computational Statistics, Bd. 28, Nr. 3: S. 1017-1034