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Veröffentlichungsdatum
Anzahl der Publikationen: 211
2023
Fahrmeir, Ludwig; Kauermann, Göran; Tutz, Gerhard 
ORCID: https://orcid.org/0000-0002-6628-3539 und Windmann, Michael
(2023):
Spatial smoothing revisited: An application to rental data in Munich.
In: Statistical Modelling, Bd. 23, Nr. 5-6: S. 480-494
[PDF, 1MB]
ORCID: https://orcid.org/0000-0002-6628-3539 und Windmann, Michael
(2023):
Spatial smoothing revisited: An application to rental data in Munich.
In: Statistical Modelling, Bd. 23, Nr. 5-6: S. 480-494
[PDF, 1MB]
Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539 und Jordan, Pascal
(2023):
Latent Trait Item Response Models for Continuous Responses.
In: Journal of Educational and Behavioral Statistics [Forthcoming]
ORCID: https://orcid.org/0000-0002-6628-3539 und Jordan, Pascal
(2023):
Latent Trait Item Response Models for Continuous Responses.
In: Journal of Educational and Behavioral Statistics [Forthcoming]
2022
Tutz, Gerhard
(2022):
Flexible Item Response Models for Count Data: The Count Thresholds Model.
In: Applied Psychological Measurement, Bd. 46, Nr. 8: S. 643-661
Tutz, Gerhard und Berger, Moritz
(2022):
Sparser Ordinal Regression Models Based on Parametric and Additive Location-Shift Approaches.
In: International Statistical Review, Bd. 90, Nr. 2: S. 306-327
Tutz, Gerhard
(2022):
Probability and non-probability samples: Improving regression modeling by using data from different sources.
In: Information Sciences, Bd. 621: S. 424-436
Faisal, Shahla und Tutz, Gerhard
(2022):
Nearest neighbor imputation for categorical data by weighting of attributes.
In: Information Sciences, Bd. 592: S. 306-319
Mauerer, Ingrid und Tutz, Gerhard
(2022):
Heterogeneity in general multinomial choice models.
In: Statistical Methods and Applications, Bd. 32, Nr. 1: S. 129-148
Tutz, Gerhard
(2022):
Item Response Thresholds Models: A General Class of Models for Varying Types of Items.
In: Psychometrika, Bd. 87, Nr. 4: S. 1238-1269
[PDF, 1MB]
Schauberger, Gunther und Tutz, Gerhard
(2022):
Multivariate ordinal random effects models including subject and group specific response style effects.
In: Statistical Modelling, Bd. 22, Nr. 5, 1471082X20978034: S. 409-429
2021
Tutz, Gerhard und Berger, Moritz
(2021):
Tree-structured scale effects in binary and ordinal regression.
In: Statistics and Computing, Bd. 31, Nr. 2, 17
Tutz, Gerhard
(2021):
Ordinal Trees and Random Forests: Score-Free Recursive Partitioning and Improved Ensembles.
In: Journal of Classification
[PDF, 1MB]
Colombi, Roberto; Giordano, Sabrina und Tutz, Gerhard
(2021):
A Rating Scale Mixture Model to Account for the Tendency to Middle and Extreme Categories.
In: Journal of Educational and Behavioral Statistics, Bd. 46, Nr. 6, 1076998621992554: S. 682-716
Faisal, Shahla und Tutz, Gerhard
(2021):
Imputation methods for high-dimensional mixed-type datasets by nearest neighbors.
In: Computers in Biology and Medicine, Bd. 135, 104577
Faisal, Shahla und Tutz, Gerhard
(2021):
Multiple imputation using nearest neighbor methods.
In: Information Sciences, Bd. 570: S. 500-516
Tutz, Gerhard
(2021):
Uncertain Choices: The Heterogeneous Multinomial Logit Model.
In: Sociological Methodology, Vol 51, Bd. 51, Nr. 1: S. 86-111
Tutz, Gerhard
(2021):
Ordinal regression: A review and a taxonomy of models.
In: Wiley Interdisciplinary Reviews-Computational Statistics, Bd. 14, Nr. 2, e1545
2020
Tutz, Gerhard und Berger, Moritz
(2020):
The effect of explanatory variables on income: A tool that allows a closer look at the differences in income.
In: Econometrics and Statistics, Bd. 16: S. 28-41
Simone, Rosaria; Tutz, Gerhard und Iannario, Maria
(2020):
Subjective heterogeneity in response attitude for multivariate ordinal outcomes.
In: Econometrics and Statistics, Bd. 14: S. 145-158
Tutz, Gerhard
(2020):
On the structure of ordered latent trait models.
In: Journal of Mathematical Psychology, Bd. 96, 102346
Tutz, Gerhard und Schauberger, Gunther
(2020):
Uncertainty in Latent Trait Models.
In: Applied Psychological Measurement, Bd. 44, Nr. 6: S. 447-464
Tutz, Gerhard
(2020):
Hierarchical Models for the Analysis of Likert Scales in Regression and Item Response Analysis.
In: International Statistical Review, Bd. 89, Nr. 1: S. 18-35
[PDF, 599kB]
2019
Tutz, Gerhard und Draxler, Clemens
(30. Oktober 2019):
A Common Framework for Classical and
Tree-Based Item Response Models Including
Extended Hierarchically Structured Models.
Department of Statistics: Technical Reports, Nr. 227
[PDF, 520kB]
Schneider, Micha; Pößnecker, Wolfgang und Tutz, Gerhard
(6. August 2019):
Variable Selection in Mixture Models with an Uncertainty Component.
Department of Statistics: Technical Reports, Nr. 225
[PDF, 805kB]
Tutz, Gerhard
(3. Januar 2019):
Modelling Heterogeneity: On the Problem of Group Comparisons with Logistic Regression and the Potential of the Heterogeneous Choice Model.
Department of Statistics: Technical Reports, Nr. 220
[PDF, 477kB]
Tutz, Gerhard und Schneider, Micha
(2019):
Flexible uncertainty in mixture models for ordinal responses.
In: Journal of Applied Statistics, Bd. 46, Nr. 9: S. 1582-1601
Berger, Moritz; Tutz, Gerhard und Schmid, Matthias
(2019):
Tree-structured modelling of varying coefficients.
In: Statistics and Computing, Bd. 29, Nr. 2: S. 217-229
Tutz, Gerhard
(2019):
Modelling heterogeneity: on the problem of group comparisons with logistic regression and the potential of the heterogeneous choice model.
In: Advances in Data Analysis and Classification
Puth, Marie-Therese; Tutz, Gerhard; Heim, Nils; Muenster, Eva; Schmid, Matthias und Berger, Moritz
(2019):
Tree-based modeling of time-varying coefficients in discrete time-to-event models.
In: Lifetime Data Analysis, Bd. 26, Nr. 3: S. 545-572
Schauberger, Gunther und Tutz, Gerhard
(2019):
BTLLasso: A Common Framework and Software Package for the Inclusion and Selection of Covariates in Bradley-Terry Models.
In: Journal of Statistical Software, Bd. 88, Nr. 9
2018
Tutz, Gerhard
(20. Dezember 2018):
On the Construction of Adjacent Categories Latent Trait Models from Binary Variables, Motivating Processes and the Interpretation of
Parameters.
Department of Statistics: Technical Reports, Nr. 218
[PDF, 449kB]
Tutz, Gerhard und Schauberger, Gunther
(24. September 2018):
Uncertainty as Response Style in Latent Trait Models.
Department of Statistics: Technical Reports, Nr.
217,
[PDF, 543kB]
Tutz, Gerhard; Schauberger, Gunther und Berger, Moritz
(2018):
Response Styles in the Partial Credit Model.
In: Applied Psychological Measurement
[PDF, 1MB]
Tutz, Gerhard
(2018):
Binary Response Models with Underlying Heterogeneity: Identification and Interpretation of Effects.
In: European Sociological Review, Bd. 34, Nr. 2: S. 211-221
Schmid, Matthias; Tutz, Gerhard und Welchowski, Thomas
(2018):
Discrimination measures for discrete time-to-event predictions.
In: Econometrics and Statistics, Bd. 7: S. 153-164
Tutz, Gerhard und Berger, Moritz
(2018):
Tree-structured modelling of categorical predictors in generalized additive regression.
In: Advances in Data Analysis and Classification, Bd. 12, Nr. 3: S. 737-758
Berger, Moritz und Tutz, Gerhard
(2018):
Tree-Structured Clustering in Fixed Effects Models.
In: Journal of Computational and Graphical Statistics, Bd. 27, Nr. 2: S. 380-392
Simone, Rosaria und Tutz, Gerhard
(2018):
Modelling uncertainty and response styles in ordinal data.
In: Statistica Neerlandica, Bd. 72, Nr. 3: S. 224-245
Bollmann, Stella; Berger, Moritz und Tutz, Gerhard
(2018):
Item-Focused Trees for the Detection of Differential Item Functioning in Partial Credit Models.
In: Educational and Psychological Measurement, Bd. 78, Nr. 5: S. 781-804
[PDF, 347kB]
2017
Drießlein, David; Küchenhoff, Helmut ORCID: https://orcid.org/0000-0002-6372-2487; Tutz, Gerhard und Wippert, Pia Maria
(1. September 2017):
Variable Selection and Inference in a
follow-up Study on Back Pain.
Department of Statistics: Technical Reports, Nr. 211
[PDF, 550kB]
ORCID: https://orcid.org/0000-0002-6372-2487; Tutz, Gerhard und Wippert, Pia Maria
(1. September 2017):
Variable Selection and Inference in a
follow-up Study on Back Pain.
Department of Statistics: Technical Reports, Nr. 211
[PDF, 550kB]
Drießlein, David; Küchenhoff, Helmut ORCID: https://orcid.org/0000-0002-6372-2487; Tutz, Gerhard und Wippert, Pia Maria
(31. August 2017):
Variable selection and inference in a follow-up study on back pain.
Department of Statistics: Technical Reports, Nr. 206
[PDF, 519kB]
ORCID: https://orcid.org/0000-0002-6372-2487; Tutz, Gerhard und Wippert, Pia Maria
(31. August 2017):
Variable selection and inference in a follow-up study on back pain.
Department of Statistics: Technical Reports, Nr. 206
[PDF, 519kB]
Tutz, Gerhard und Schneider, Micha
(24. Februar 2017):
Mixture Models for Ordinal Responses with a Flexible Uncertainty Component.
Department of Statistics: Technical Reports, Nr. 203
[PDF, 575kB]
Schauberger, Gunther und Tutz, Gerhard
(17. Januar 2017):
BTLLasso - A Common Framework and Software Package for the Inclusion and Selection of Covariates in Bradley-Terry Models.
Department of Statistics: Technical Reports, Nr. 202
[PDF, 593kB]
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]
Groll, Andreas; Hastie, Trevor und Tutz, Gerhard
(2017):
Selection of Effects in Cox Frailty Models by Regularization Methods.
In: Biometrics, Bd. 73, Nr. 3: S. 846-856
Tutz, Gerhard; Schneider, Micha; Iannario, Maria und Piccolo, Domenico
(2017):
Mixture models for ordinal responses to account for uncertainty of choice.
In: Advances in Data Analysis and Classification, Bd. 11, Nr. 2: S. 281-305
Faisal, Shahla und Tutz, Gerhard
(2017):
Missing value imputation for gene expression data by tailored nearest neighbors.
In: Statistical Applications in Genetics and Molecular Biology, Bd. 16, Nr. 2: S. 95-106
Groll, Andreas und Tutz, Gerhard
(2017):
Variable selection in discrete survival models including heterogeneity.
In: Lifetime Data Analysis, Bd. 23, Nr. 2: S. 305-338
Oelker, Margret-Ruth und Tutz, Gerhard
(2017):
A uniform framework for the combination of penalties in generalized structured models.
In: Advances in Data Analysis and Classification, Bd. 11, Nr. 1: S. 97-120
2016
Schauberger, Gunther; Groll, Andreas und Tutz, Gerhard
(25. August 2016):
Modeling Football Results in the German Bundesliga Using Match-specific Covariates.
Department of Statistics: Technical Reports, Nr. 197
[PDF, 560kB]
Tutz, Gerhard; Schauberger, Gunther und Berger, Moritz
(23. August 2016):
Response Styles in the Partial Credit Model.
Department of Statistics: Technical Reports, Nr. 196
[PDF, 770kB]
Groll, Andreas ORCID: https://orcid.org/0000-0002-6628-3539; Hastie, Trevor und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(25. Februar 2016):
Regularization in Cox Frailty Models.
Department of Statistics: Technical Reports, Nr. 191
[PDF, 8MB]
ORCID: https://orcid.org/0000-0002-6628-3539; Hastie, Trevor und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(25. Februar 2016):
Regularization in Cox Frailty Models.
Department of Statistics: Technical Reports, Nr. 191
[PDF, 8MB]
Tutz, Gerhard und Moritz, Berger
(22. Februar 2016):
Separating Location and Dispersion in Ordinal Regression Models.
Department of Statistics: Technical Reports, Nr. 190
[PDF, 632kB]
Pößnecker, Wolfgang und Tutz, Gerhard
(18. Januar 2016):
A General Framework for the Selection of Effect Type in Ordinal Regression.
Department of Statistics: Technical Reports, Nr. 186
[PDF, 625kB]
Tutz, Gerhard und Berger, Moritz
(2016):
Item-focussed Trees for the Identification of Items in Differential Item Functioning.
In: Psychometrika, Bd. 81, Nr. 3: S. 727-750
Tutz, Gerhard und Berger, Moritz
(2016):
Response Styles in Rating Scales: Simultaneous Modeling of Content-Related Effects and the Tendency to Middle or Extreme Categories.
In: Journal of Educational and Behavioral Statistics, Bd. 41, Nr. 3: S. 239-268
[PDF, 679kB]
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
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
Janitza, Silke; Tutz, Gerhard und Boulesteix, Anne-Laure
(2016):
Random forest for ordinal responses: Prediction and variable selection.
In: Computational Statistics and Data Analysis, Bd. 96: S. 57-73
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
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
Möller, Annette; Tutz, Gerhard und Gertheiss, Jan
(2016):
Random forests for functional covariates.
In: Journal of Chemometrics, Bd. 30, Nr. 12: S. 715-725
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]
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 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
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
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 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 Gertheiss, Jan
(2016):
Regularized Regression for Categorical Data.
In: Statistical Modelling, Bd. 16, Nr. 3: S. 161-200
[PDF, 832kB]
2015
Schauberger, Gunther und Tutz, Gerhard
(19. August 2015):
Modelling Heterogeneity in Paired Comparison Data - an L1 Penalty Approach with an Application to Party Preference Data.
Department of Statistics: Technical Reports, Nr. 183
[PDF, 440kB]
Janitza, Silke und Tutz, Gerhard
(2. Januar 2015):
Prediction Models for Time Discrete Competing Risks.
Department of Statistics: Technical Reports, Nr. 177
[PDF, 552kB]
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]
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
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]
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]
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: AStA Advances in Statistical Analysis, Bd. 99, Nr. 2: S. 209-227
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
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
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
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
Möst, Susanne; Pößnecker, Wolfgang und Tutz, Gerhard
(2015):
Variable selection for discrete competing risks models.
In: Quality & Quantity: S. 1-22
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
2014
Tutz, Gerhard; Schneider, Micha; Iannario, Maria und Piccolo, Domenico
(16. Dezember 2014):
Mixture Models for Ordinal Responses to Account for Uncertainty of Choice.
Department of Statistics: Technical Reports, Nr. 175
[PDF, 597kB]
Janitza, Silke; Tutz, Gerhard und Boulesteix, Anne-Laure
(1. Dezember 2014):
Random Forests for Ordinal Response Data: Prediction and Variable Selection.
Department of Statistics: Technical Reports, Nr. 174
[PDF, 597kB]
Tutz, Gerhard und Oelker, Margret-Ruth
(30. Oktober 2014):
Modeling Clustered Heterogeneity: Fixed Effects, Random Effects and Mixtures.
Department of Statistics: Technical Reports, Nr. 156
[PDF, 649kB]
Tutz, Gerhard und Ramzan, Shahla
(13. Oktober 2014):
Improved Methods for the Imputation of Missing Data by Nearest Neighbor Methods.
Department of Statistics: Technical Reports, Nr. 172
[PDF, 672kB]
Tutz, Gerhard und Moritz, Berger
(12. August 2014):
Tree-Structured Modelling of Categorical Predictors in Regression.
Department of Statistics: Technical Reports, Nr. 169
[PDF, 573kB]
Groll, Andreas; Schauberger, Gunther und Tutz, Gerhard
(2. Juli 2014):
Brazil or Germany - who will win the trophy? Prediction of the FIFA World Cup 2014 based on team-specific regularized Poisson regression.
Department of Statistics: Technical Reports, Nr. 166
[PDF, 634kB]
Casalicchio, Giuseppe; Tutz, Gerhard und Schauberger, Gunther
(28. Mai 2014):
Subject-specific Bradley-Terry-Luce Models with Implicit Variable Selection.
Department of Statistics: Technical Reports, Nr. 160
[PDF, 396kB]
Möst, Stephanie; Pößnecker, Wolfgang und Tutz, Gerhard
(28. Mai 2014):
Variable Selection for Discrete Competing Risks Models.
Department of Statistics: Technical Reports, Nr. 161
[PDF, 729kB]
Mauerer, Ingrid; Pößnecker, Wolfgang; Thurner, Paul W. und Tutz, Gerhard
(9. April 2014):
Modeling electoral choices in multiparty systems with high-dimensional data: A regularized selection of parameters using the Lasso approach.
Department of Statistics: Technical Reports, Nr. 158
[PDF, 709kB]
Hess, Wolfgang; Tutz, Gerhard und Gertheiss, Jan
(23. Februar 2014):
A Flexible Link Function for Discrete-Time Duration Models.
Department of Statistics: Technical Reports, Nr. 155
[PDF, 626kB]
Tutz, Gerhard und Schauberger, Gunther
(7. Januar 2014):
Extended Ordered Paired Comparison Models with
Application to Football Data from German Bundesliga.
Department of Statistics: Technical Reports, Nr. 151
[PDF, 538kB]
Tutz, Gerhard und Groll, Andreas
(2014):
Variable Selection in Discrete Survival Models Including Heterogeneity.
Department of Statistics: Technical Reports, Nr. 167
[PDF, 571kB]
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
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
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
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
Heinzl, Felix und Tutz, Gerhard
(2014):
Additive mixed models with approximate Dirichlet process mixtures: the EM approach.
In: Statistics and Computing: S. 1-20
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]
2013
Tutz, Gerhard und Petry, Sebastian
(21. Mai 2013):
Generalized Additive Models with Unknown Link Function Including Variable Selection.
Department of Statistics: Technical Reports, Nr. 145
[PDF, 2MB]
Oelker, Margret-Ruth und Tutz, Gerhard
(11. März 2013):
A General Family of Penalties for Combining Differing Types of Penalties in Generalized Structured Models.
Department of Statistics: Technical Reports, Nr. 139
[PDF, 802kB]
Heinzl, Felix und Tutz, Gerhard
(14. Februar 2013):
Clustering in Additive Mixed Models with
Approximate Dirichlet Process Mixtures using the EM Algorithm.
Department of Statistics: Technical Reports, Nr. 138
[PDF, 1MB]
Heinzl, Felix und Tutz, Gerhard
(Februar 2013):
Clustering in linear mixed models with approximate Dirichlet process mixtures using EM algorithm.
In: Statistical Modelling, Bd. 13, Nr. 1: S. 41-67
[PDF, 555kB]
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
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 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 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
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
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
2012
Tutz, Gerhard und Schauberger, Gunther
(7. Dezember 2012):
A Penalty Approach to Differential Item
Functioning in Rasch Models.
Department of Statistics: Technical Reports, Nr. 134
[PDF, 588kB]
Tutz, Gerhard; Pößnecker, Wolfgang und Uhlmann, Lorenz
(21. Juni 2012):
Variable Selection in General Multinomial Logit Models.
Department of Statistics: Technical Reports, Nr. 126
[PDF, 567kB]
Heinzl, Felix und Tutz, Gerhard
(12. Juni 2012):
Clustering in linear mixed models with a group fused lasso penalty.
Department of Statistics: Technical Reports, Nr. 123
[PDF, 606kB]
Tutz, Gerhard und Schauberger, Gunther
(2. April 2012):
Visualization of Categorical Response Models - from Data Glyphs to Parameter Glyphs.
Department of Statistics: Technical Reports, Nr. 117
[PDF, 975kB]
Oelker, Margret-Ruth; Gertheiss, Jan und Tutz, Gerhard
(6. März 2012):
Regularization and Model Selection with Categorial Predictors and Effect Modifiers in Generalized Linear Models.
Department of Statistics: Technical Reports, Nr. 122
[PDF, 596kB]
Gertheiss, Jan und Tutz, Gerhard
(2012):
Regularization and Model Selection with Categorial Effect Modifiers.
In: Statistica Sinica, Bd. 22: S. 957-982
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
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
Oelker, Magret-Ruth; Gertheiss, Jan und Tutz, Gerhard
(2012):
Categorial effect modifiers in generalized linear models.
20th International Conference on COMPUTATIONAL STATISTICS (COMPSTAT 2012), Limassol, 27.-31. August 2012.
Colubi, Ana; Fokianos, Konstantinos; Kontoghiorghes, Erricos John und Gonzalez-Rodriguez, G. (Hrsg.):
In: Proceedings of COMPSTAT 2012,
Petry, Sebastian und Tutz, Gerhard
(2012):
Shrinkage and Variable Selection by Polytopes.
In: Journal of Statistical Planning and Inference, Bd. 142: S. 48-64
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
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,
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
2011
Heinzl, Felix und Tutz, Gerhard
(17. November 2011):
Clustering in linear mixed models with Dirichlet process mixtures using EM algorithm.
Department of Statistics: Technical Reports, Nr. 115
[PDF, 698kB]
Groll, Andreas ORCID: https://orcid.org/0000-0002-6628-3539 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(3. Juni 2011):
Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation.
Department of Statistics: Technical Reports, Nr. 108
[PDF, 4MB]
ORCID: https://orcid.org/0000-0002-6628-3539 und Tutz, Gerhard ORCID: https://orcid.org/0000-0002-6628-3539
(3. Juni 2011):
Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation.
Department of Statistics: Technical Reports, Nr. 108
[PDF, 4MB]
Groll, Andreas und Tutz, Gerhard
(Juni 2011):
Regularization for Generalized Additive Mixed Models by Likelihood-Based Boosting.
Department of Statistics: Technical Reports, Nr. 110
[PDF, 5MB]
Petry, Sebastian; Flexeder, Claudia und Tutz, Gerhard
(2. März 2011):
Pairwise Fused Lasso.
Department of Statistics: Technical Reports, Nr. 102
[PDF, 745kB]
Ulbricht, Jan und Tutz, Gerhard
(2011):
Combining Quadratic Penalization and Variable Selection via Forward Boosting.
Department of Statistics: Technical Reports, Nr. 99
[PDF, 1MB]
Zahid, Faisal Maqbool und Tutz, Gerhard
(2011):
Proportional Odds Models with High-dimensional Data Structure.
Department of Statistics: Technical Reports, Nr. 100
[PDF, 989kB]
Petry, Sebastian und Tutz, Gerhard
(2011):
The OSCAR for Generalized Linear Models.
Department of Statistics: Technical Reports, Nr. 112
[PDF, 745kB]
Leitenstorfer, Florian und Tutz, Gerhard
(2011):
Estimation of Single-Index Models Based on Boosting Techniques.
In: Statistical Modelling, Bd. 11: S. 203-217
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
Tutz, Gerhard
(2011):
Poisson Regression.
In: Lovric, Miodrag (Hrsg.):
International Encyclopedia of Statistical Sciences. Berlin: Springer. S. 1075-1077
2010
Tutz, Gerhard und Groll, Andreas
(Dezember 2010):
Binary and Ordinal Random Effects Models Including Variable Selection.
Department of Statistics: Technical Reports, Nr. 97
[PDF, 1MB]
Tutz, Gerhard und Petry, Sebastian
(9. Juli 2010):
Nonparametric Estimation of the Link Function Including Variable Selection.
Department of Statistics: Technical Reports, Nr. 85
[PDF, 3MB]
Heumann, Christian und Grenke, Moritz
(2010):
An efficient model averaging procedure for logistic regression models using a bayesian estimator with laplace prior.
In: Kneib, Thomas und Tutz, Gerhard (Hrsg.):
Statistical Modelling and Regression Structures - Festschrift in Honour of Ludwig Fahrmeir. Heidelberg: Physica-Verlag. S. 79-90
Höhle, Michael
(2010):
Online Changepoint Detection in Categorical Time Series.
In: Kneib, Thomas und Tutz, Gerhard (Hrsg.):
Statistical Modelling and Regression Structures - Festschrift in Honour of Ludwig Fahrmeir. Berlin, Heidelberg: Physica-Verlag. S. 377-397
Kneib, Thomas und Tutz, Gerhard (Hrsg.)
(2010):
Statistical Modelling and Regression Structures - Festschrift in Honour of Ludwig Fahrmeir.
Berlin; Heidelberg u.a.: Physica-Verlag.
Mansmann, Ulrich; Schmidberger, Markus; Strobl, Ralf und Jurinovic, Vindi
(2010):
Indirect Comparison of Interaction Graphs.
In: Kneib, Thomas und Tutz, Gerhard (Hrsg.):
Statistical Modelling and Regression Structures -- Festschrift in Honour of Ludwig Fahrmeir. Physica-Verlag. S. 472
Robinzonov, Nikolay; Tutz, Gerhard und Hothorn, Torsten
(2010):
Boosting Techniques for Nonlinear Time Series Models.
Department of Statistics: Technical Reports, Nr. 75
[PDF, 2MB]
Zahid, Faisal Maqbool und Tutz, Gerhard
(2010):
Multinomial Logit Models with Implicit Variable Selection.
Department of Statistics: Technical Reports, Nr. 89
[PDF, 461kB]
Gertheiss, Jan und Tutz, Gerhard
(2010):
Regularization and Model Selection with Categorial Effect Modifiers.
Department of Statistics: Technical Reports, Nr. 73
Statistica Sinica (to appear)
[PDF, 2MB]
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
Gertheiss, Jan und Tutz, Gerhard
(2010):
Sparse modeling of categorial explanatory variables.
In: The Annals of Applied Statistics, Bd. 4: S. 2150-2180
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
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 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 Strobl, Carolin
(2010):
Generalisierte lineare Modelle.
In: Schmitz, Bernhard und Holling, Heinz (Hrsg.):
Handbuch der psychologischen Methoden und Evaluation. Göttingen: Hogrefe Verlag. S. 461-471
2009
Zahid, Faisal Maqbool und Tutz, Gerhard
(September 2009):
Ridge Estimation for Multinomial Logit Models with Symmetric Side Constraints.
Department of Statistics: Technical Reports, Nr. 67
[PDF, 287kB]
Gertheiss, Jan; Hogger, Sara; Oberhauser, Cornelia und Tutz, Gerhard
(Juli 2009):
Selection of Ordinally Scaled Independent Variables.
Department of Statistics: Technical Reports, Nr. 62
Applied Statistics (accepted for publication)
[PDF, 2MB]
Petry, Sebastian und Tutz, Gerhard
(7. April 2009):
Shrinkage and Variable Selection by Polytopes.
Department of Statistics: Technical Reports, Nr. 53
[PDF, 963kB]
Strobl, Carolin; Malley, James und Tutz, Gerhard
(April 2009):
An Introduction to Recursive Partitioning: Rationale, Application and Characteristics of Classification and Regression Trees, Bagging and Random Forests.
Department of Statistics: Technical Reports, Nr. 55
[PDF, 974kB]
Slawski, Martin; Castell, Wolfgang zu und Tutz, Gerhard
(9. März 2009):
Feature Selection Guided by Structural Information.
Department of Statistics: Technical Reports, Nr. 51
[PDF, 1MB]
Gertheiss, Jan und Tutz, Gerhard
(2009):
Sparse Modeling of Categorial Explanatory Variables.
Department of Statistics: Technical Reports, Nr. 60
The Annals of Applied Statistics, 4
[PDF, 2MB]
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
(2009):
Statistische Tests.
In: Schwaiger, Manfred und Meyer, Anton (Hrsg.):
Theorien und Methoden der Betriebswirtschaft. München: Vahlen. S. 439-454
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
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
Shafik, Nivien und Tutz, Gerhard
(2009):
Boosting nonlinear additive autoregressive time series.
In: Computational Statistics & Data Analysis, Bd. 53: S. 2453-2464
Strobl, Carolin; Malley, James und Tutz, Gerhard
(2009):
An introduction to recursive partitioning: Rationale, application and characteristics of classification and regression trees, bagging and random forests.
In: Psychological Methods, Bd. 14, Nr. 4: S. 323-348
Tutz, Gerhard und Ulbricht, Jan
(2009):
Penalized regression with correlation based penalty.
In: Statistics and Computing, Bd. 19: S. 239-253
2008
Leitenstorfer, Florian und Tutz, Gerhard
(20. Juni 2008):
Estimation of Single-Index Models Based on Boosting Techniques.
Department of Statistics: Technical Reports, Nr. 34
[PDF, 782kB]
Gertheiss, Jan und Tutz, Gerhard
(19. Juni 2008):
Feature Selection and Weighting by Nearest Neighbor Ensembles.
Department of Statistics: Technical Reports, Nr. 33
Chemometrics and Intelligent Laboratory Systems, 99
[PDF, 2MB]
Gertheiss, Jan und Tutz, Gerhard
(9. Januar 2008):
Penalized Regression with Ordinal Predictors.
Department of Statistics: Technical Reports, Nr. 15
International Statistical Review, 77
[PDF, 2MB]
2007
Tutz, Gerhard und Gertheiss, Jan
(20. Dezember 2007):
Feature Extraction in Signal Regression: A Boosting Technique for Functional Data Regression.
Department of Statistics: Technical Reports, Nr. 11
Journal of Computational and Graphical Statistics, 19
[PDF, 2MB]
Ulbricht, Jan und Tutz, Gerhard
(11. Dezember 2007):
Boosting Correlation Based Penalization in Generalized Linear Models.
Department of Statistics: Technical Reports, Nr. 9
[PDF, 718kB]
Kneib, Thomas; Hothorn, Torsten und Tutz, Gerhard
(2007):
Variable Selection and Model Choice in Geoadditive Regression Models.
Department of Statistics: Technical Reports, Nr. 3
[PDF, 1MB]
Shafik, Nivien und Tutz, Gerhard
(2007):
Boosting Nonlinear Additive Autoregressive Time Series.
Department of Statistics: Technical Reports, Nr. 6
[PDF, 776kB]
2006
Leitenstorfer, Florian und Tutz, Gerhard
(2006):
Smoothing with Curvature Constraints based on Boosting Techniques.
Sonderforschungsbereich 386, Discussion Paper 467
[PDF, 319kB]
Leitenstorfer, Florian und Tutz, Gerhard
(2006):
Knot selection by boosting techniques.
Sonderforschungsbereich 386, Discussion Paper 481
[PDF, 654kB]
Reithinger, Florian; Jank, Wolfgang; Tutz, Gerhard und Shmueli, Galit
(2006):
Smoothing sparse and unevenly sampled curves using semiparametric mixed models: An application to online auctions.
Sonderforschungsbereich 386, Discussion Paper 483
[PDF, 839kB]
Krämer, N.; Boulesteix, Anne-Laure und Tutz, Gerhard
(2006):
Penalized Partial Least Squares Based on B-Splines Transformations.
Sonderforschungsbereich 386, Discussion Paper 485
[PDF, 392kB]
Tutz, Gerhard und Ulbricht, Jan
(2006):
Penalized Regression with Correlation Based Penalty.
Sonderforschungsbereich 386, Discussion Paper 486
[PDF, 472kB]
2005
Tutz, Gerhard und Leitenstorfer, Florian
(2005):
Generalized smooth monotonic regression.
Sonderforschungsbereich 386, Discussion Paper 417
[PDF, 1MB]
Tutz, Gerhard und Binder, Harald
(2005):
Boosting Ridge Regression.
Sonderforschungsbereich 386, Discussion Paper 418
[PDF, 1MB]
Leitenstorfer, Florian und Tutz, Gerhard
(2005):
Generalized Monotonic Regression Based on B-Splines with an Application to Air Pollution Data.
Sonderforschungsbereich 386, Discussion Paper 444
[PDF, 681kB]
Tutz, Gerhard und Reithinger, Florian
(2005):
Flexible semiparametric mixed models.
Sonderforschungsbereich 386, Discussion Paper 448
[PDF, 1MB]
2004
Boulesteix, Anne-Laure und Tutz, Gerhard
(2004):
Identification of Interaction Patterns and Classification with Applications to Microarray Data.
Sonderforschungsbereich 386, Discussion Paper 369
[PDF, 317kB]
Tutz, Gerhard und Binder, Harald
(2004):
Localized Regression.
Sonderforschungsbereich 386, Discussion Paper 378
[PDF, 312kB]
Krause, Rüdiger und Tutz, Gerhard
(2004):
Simultaneous selection of variables and smoothing parameters by genetic algorithms.
Sonderforschungsbereich 386, Discussion Paper 389
[PDF, 896kB]
Krause, Rüdiger und Tutz, Gerhard
(2004):
Variable selection and discrimination in gene expression data by genetic algorithms.
Sonderforschungsbereich 386, Discussion Paper 390
[PDF, 401kB]
Linde, A. van der und Tutz, Gerhard
(2004):
On association in regression: the coefficient of determination revisited.
Sonderforschungsbereich 386, Discussion Paper 391
[PDF, 390kB]
Einbeck, Jochen und Tutz, Gerhard
(2004):
Modelling beyond Regression Functions: an Application of Multimodal Regression to Speed-Flow Data.
Sonderforschungsbereich 386, Discussion Paper 395
[PDF, 437kB]
Tutz, Gerhard und Binder, Harald
(2004):
Generalized additive modelling with implicit variable selection by likelihood based boosting.
Sonderforschungsbereich 386, Discussion Paper 401
[PDF, 370kB]
2003
Tutz, Gerhard und Scholz, T.
(2003):
Ordinal regression modelling between proportional odds and non-proportional odds.
Sonderforschungsbereich 386, Discussion Paper 304
[PDF, 407kB]
Krause, Rüdiger und Tutz, Gerhard
(2003):
Additive Modelling with Penalized Regression Splines and Genetic Algorithms.
Sonderforschungsbereich 386, Discussion Paper 312
[PDF, 652kB]
Boulesteix, Anne-Laure und Tutz, Gerhard
(2003):
A Framework to Discover Emerging Patterns for Application in Microarray Data.
Sonderforschungsbereich 386, Discussion Paper 313
[PDF, 232kB]
Tutz, Gerhard
(2003):
Response smoothing estimators in binary regression.
Sonderforschungsbereich 386, Discussion Paper 318
[PDF, 460kB]
Einbeck, Jochen; Tutz, Gerhard und Evers, L.
(2003):
Local Principal Curves.
Sonderforschungsbereich 386, Discussion Paper 320
[PDF, 445kB]
Tutz, Gerhard und Hechenbichler, K.
(2003):
Aggregating Classifiers With Ordinal Response Structure.
Sonderforschungsbereich 386, Discussion Paper 359
[PDF, 369kB]
2002
Tutz, Gerhard und Binder, Harald
(2002):
Flexible Modelling of Discrete Failure Time Including Time-Varying Smooth Effects.
Sonderforschungsbereich 386, Discussion Paper 294
[PDF, 361kB]
Tutz, Gerhard
(2002):
Modelling of repeated ordered measurements by isotonic sequential regression.
Sonderforschungsbereich 386, Discussion Paper 298
[PDF, 244kB]
2001
Kauermann, Göran und Tutz, Gerhard
(2001):
Vanishing of Risk Factors for the Success and Survival of Newly Founded Companies.
Sonderforschungsbereich 386, Discussion Paper 242
[PDF, 343kB]
Tutz, Gerhard
(2001):
Generalized semiparametrically structured ordinal models.
Sonderforschungsbereich 386, Discussion Paper 250
[PDF, 445kB]
Tutz, Gerhard
(2001):
Generalized semiparametrically structured mixed models.
Sonderforschungsbereich 386, Discussion Paper 251
[PDF, 436kB]
2000
Kauermann, Göran und Tutz, Gerhard
(2000):
Semiparametric Modeling of Ordinal Data.
Sonderforschungsbereich 386, Discussion Paper 193
[PDF, 353kB]
Tutz, Gerhard und Scholz, T.
(2000):
Semiparametric Modelling of Multicategorical Data.
Sonderforschungsbereich 386, Discussion Paper 209
[PDF, 313kB]
1999
Kauermann, Göran und Tutz, Gerhard
(1999):
Testing Generalized Linear and Semiparametric Models Against Smooth Alternatives.
Sonderforschungsbereich 386, Discussion Paper 149
[PDF, 385kB]
Dreesman, J. und Tutz, Gerhard
(1999):
Nonstationary conditional models for spatial data based on varying coefficients.
Sonderforschungsbereich 386, Discussion Paper 150
[PDF, 287kB]
Tutz, Gerhard; Edlich, Silke und Bäumer, Christoph
(1999):
Comparison between local estimates for multi-categorical varying-coefficent models.
Sonderforschungsbereich 386, Discussion Paper 151
[PDF, 299kB]