Gerhard Tutz

发表

Boosting techniques for nonlinear time series models

Gerhard Tutz, Torsten Hothorn, Nikolay Robinzonov, 2012 .

Local principal curves

Gerhard Tutz, Jochen Einbeck, Ludger Evers, 2005, Stat. Comput..

Multiple-Spell Analysis

Gerhard Tutz, Matthias Schmid, G. Tutz, 2016 .

Poisson Regression

Gerhard Tutz, 2011, International Encyclopedia of Statistical Science.

State Space and Hidden Markov Models

Gerhard Tutz, Ludwig Fahrmeir, 2001 .

A CART-based approach to discover emerging patterns in microarray data

Gerhard Tutz, Anne-Laure Boulesteix, Korbinian Strimmer, 2003, Bioinform..

Tree-structured modelling of categorical predictors in generalized additive regression

Gerhard Tutz, Moritz Berger, G. Tutz, 2017, Advances in Data Analysis and Classification.

Variable selection and inference in a follow-up study on back pain

Gerhard Tutz, Helmut Küchenhoff, David Drießlein, 2017 .

Boosting nonlinear additive autoregressive time series

Gerhard Tutz, Nivien Shafik, G. Tutz, 2009, Comput. Stat. Data Anal..

Regression for Categorical Data: Preface

Gerhard Tutz, 2011 .

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

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

Modeling electoral choices in multiparty systems with high-dimensional data: A regularized selection of parameters using the Lasso approach

Gerhard Tutz, Ingrid Mauerer, Wolfgang Pößnecker, 2015 .

Modeling Football Results in the German Bundesliga Using Match-specific Covariates

Gerhard Tutz, Gunther Schauberger, Andreas H. Groll, 2016 .

Multinomial logit models with implicit variable selection

Gerhard Tutz, Faisal Maqbool Zahid, 2013, Adv. Data Anal. Classif..

Brazil or Germany - who will win the trophy? Prediction of the FIFA World Cup 2014 based on team-specific regularized Poisson regression

Gerhard Tutz, Gunther Schauberger, Andreas H. Groll, 2014 .

Estimation of single-index models based on boosting techniques

Gerhard Tutz, Florian Leitenstorfer, G. Tutz, 2011 .

Knot selection by boosting techniques

Gerhard Tutz, Florian Leitenstorfer, G. Tutz, 2007, Comput. Stat. Data Anal..

Comparison of Maximum Likelihood with Conditional Pairwise Likelihood Estimation of Person Parameters in the Rasch Model

Gerhard Tutz, Clemens Draxler, Katharina Zink, 2016, Commun. Stat. Simul. Comput..

Binary Response Models with Underlying Heterogeneity: Identification and Interpretation of Effects

Gerhard Tutz, G. Tutz, 2018 .

A uniform framework for the combination of penalties in generalized structured models

Gerhard Tutz, Margret-Ruth Oelker, G. Tutz, 2015, Advances in Data Analysis and Classification.

Log-linear parameterizations in discriminant analysis

Gerhard Tutz, G. Tutz, 1990, ZOR Methods Model. Oper. Res..

Localized classification

Gerhard Tutz, Harald Binder, G. Tutz, 2005, Stat. Comput..

Genetic algorithms for the selection of smoothing parameters in additive models

Gerhard Tutz, Rüdiger Krause, G. Tutz, 2006, Comput. Stat..

Selecting and Checking Models

Gerhard Tutz, Ludwig Fahrmeir, 2001 .

Competing Risks Models

Gerhard Tutz, Matthias Schmid, G. Tutz, 2016 .

Item-focussed Trees for the Identification of Items in Differential Item Functioning

Gerhard Tutz, Moritz Berger, G. Tutz, 2015, Psychometrika.

Feature Selection and Weighting by Nearest Neighbor Ensembles

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

Improved nearest neighbor classifiers by weighting and selection of predictors

Gerhard Tutz, Dominik Koch, G. Tutz, 2016, Stat. Comput..

High-Dimensional Models: Structuring and Selection of Predictors

Gerhard Tutz, Matthias Schmid, G. Tutz, 2016 .

Boosting ridge regression

Gerhard Tutz, Harald Binder, G. Tutz, 2007, Comput. Stat. Data Anal..

A Penalty Approach to Differential Item Functioning in Rasch Models

Gerhard Tutz, Gunther Schauberger, G. Tutz, 2015, Psychometrika.

Response shrinkage estimators in binary regression

Gerhard Tutz, Florian Leitenstorfer, G. Tutz, 2006, Comput. Stat. Data Anal..

Smoothing for Categorical Data: Discrete Kernel Regression and Local Likelihood Approaches

Gerhard Tutz, G. Tutz, 1996 .

Smoothing sparse and unevenly sampled curves using semiparametric mixed models: An application to online auctions

Wolfgang Jank, Gerhard Tutz, Galit Shmueli, 2006 .

Subject-specific Bradley–Terry–Luce models with implicit variable selection

Gerhard Tutz, Giuseppe Casalicchio, Gunther Schauberger, 2015 .

Generalized semiparametrically structured mixed models

Gerhard Tutz, G. Tutz, 2004, Comput. Stat. Data Anal..

Nearest neighbor ensembles for functional data with interpretable feature selection

Gerhard Tutz, Jan Gertheiss, Karen Fuchs, 2015 .

Bagging, Boosting and Ordinal Classification

Gerhard Tutz, Klaus Hechenbichler, 2004, GfKl.

A comparison of methods for the fitting of generalized additive models

Gerhard Tutz, Harald Binder, G. Tutz, 2008, Stat. Comput..

Selection of effects in Cox frailty models by regularization methods.

Gerhard Tutz, Trevor Hastie, Andreas Groll, 2017, Biometrics.

Regularization Methods in Economic Forecasting

Gerhard Tutz, Gunther Schauberger, G. Tutz, 2015 .

Response Styles in Rating Scales

Gerhard Tutz, Moritz Berger, 2016 .

Discrete kernels, loss functions and parametric models in discrete discrimination: A comparative study

Gerhard Tutz, Herbert Groß, G. Tutz, 1995, Math. Methods Oper. Res..

Modeling heterogeneity by fixed effects models

Gerhard Tutz, Magret-Ruth Oelker, G. Tutz, 2013 .

Pairwise Fused Lasso

Gerhard Tutz, Sebastian Petry, Claudia Flexeder, 2011 .

Regression for Categorical Data: Bibliography

Gerhard Tutz, 2011 .

A survival tree method for the analysis of discrete event times in clinical and epidemiological studies

Gerhard Tutz, Matthias Schmid, Helmut Küchenhoff, 2016, Statistics in medicine.

Mixture models for ordinal responses to account for uncertainty of choice

Gerhard Tutz, Maria Iannario, Domenico Piccolo, 2017, Adv. Data Anal. Classif..

Modelling heterogeneity: on the problem of group comparisons with logistic regression and the potential of the heterogeneous choice model

Gerhard Tutz, 2020, Adv. Data Anal. Classif..

Extended ordered paired comparison models with application to football data from German Bundesliga

Gerhard Tutz, Gunther Schauberger, G. Tutz, 2015 .

A Framework to Discover Emerging Patterns for Application in Microarray Data

Gerhard Tutz, Anne-Laure Boulesteix, A. Boulesteix, 2003 .

Supervised feature selection in mass spectrometry-based proteomic profiling by blockwise boosting

Gerhard Tutz, Jan Gertheiss, 2009, Bioinform..

Variable selection in discrete survival models including heterogeneity

Gerhard Tutz, Andreas Groll, G. Tutz, 2017, Lifetime data analysis.

Regularization and Model Selection with Categorical Covariates

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

Regression for Categorical Data: Tree-Based Methods

Gerhard Tutz, 2011 .

Comments on The class of cub models: statistical foundations, inferential issues and empirical evidence by D. Piccolo and R. Simone

Gerhard Tutz, 2019, Stat. Methods Appl..

Generalized Linear Mixed Models Based on Boosting

Gerhard Tutz, Andreas H. Groll, G. Tutz, 2010 .

Penalized regression with correlation-based penalty

Gerhard Tutz, Jan Ulbricht, 2009, Stat. Comput..

Modeling Discrete Time-To-Event Data

Gerhard Tutz, Matthias Schmid, G. Tutz, 2016 .

Regression for Categorical Data: List of Examples

Gerhard Tutz, G. Tutz, 2011 .

Advances in GLIM and Statistical Modelling : Proceedings of the GLIM92 Conference and the 7th International Workshop on Statistical Modelling

Gerhard Tutz, Ludwig Fahrmeir, Brian Francis, 1992 .

Item-Focused Trees for the Detection of Differential Item Functioning in Partial Credit Models

Gerhard Tutz, Moritz Berger, Stella Bollmann, 2016, Educational and psychological measurement.

Variable selection for generalized linear mixed models by L1-penalized estimation

Gerhard Tutz, Andreas Groll, G. Tutz, 2012, Statistics and Computing.

Modelling Heterogeneity in Paired Comparison Data - an L1 Penalty Approach with an Application to Party Preference Data

Gerhard Tutz, Gunther Schauberger, G. Tutz, 2015 .

Improved methods for the imputation of missing data by nearest neighbor methods

Gerhard Tutz, Shahla Ramzan, G. Tutz, 2015, Comput. Stat. Data Anal..

Ridge estimation for multinomial logit models with symmetric side constraints

Gerhard Tutz, Faisal Maqbool Zahid, 2013, Comput. Stat..

Clustering in linear mixed models with Dirichlet process mixtures using EM algorithm

Gerhard Tutz, Felix Heinzl, G. Tutz, 2011 .

Basic Regression Models

Gerhard Tutz, Matthias Schmid, G. Tutz, 2016 .

Random forest for ordinal responses: Prediction and variable selection

Gerhard Tutz, Anne-Laure Boulesteix, Silke Janitza, 2016, Comput. Stat. Data Anal..

Tree-Based Approaches

Gerhard Tutz, Matthias Schmid, 2016 .

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

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

Tree-based modeling of time-varying coefficients in discrete time-to-event models

Gerhard Tutz, Matthias Schmid, Moritz Berger, 2019, Lifetime data analysis.

Visualization of Categorical Response Models: From Data Glyphs to Parameter Glyphs

Gerhard Tutz, Gunther Schauberger, G. Tutz, 2013 .

BTLLasso: A Common Framework and Software Package for the Inclusion and Selection of Covariates in Bradley-Terry Models

Gerhard Tutz, Gunther Schauberger, G. Tutz, 2019, Journal of Statistical Software.

Alternative parameterizations in business tendency surveys

Gerhard Tutz, Bernd Morawitz, 1990, ZOR Methods Model. Oper. Res..

The OSCAR for Generalized Linear Models

Gerhard Tutz, Sebastian Petry, 2011 .

Regression for Categorical Data: Constrained Estimation

Gerhard Tutz, G. Tutz, 2011 .

Variable scaling and nearest neighbor methods

Gerhard Tutz, Jan Gertheiss, 2009 .

A Boosting Approach to Generalized Monotonic Regression

Gerhard Tutz, Florian Leitenstorfer, 2006, GfKl.

Variable selection for discrete competing risks models

Gerhard Tutz, Wolfgang Pößnecker, Stephanie Möst, 2016 .

A Taxonomy of Polytomous Item Response Models

Gerhard Tutz, 2020 .

Nonparametric estimation of the link function including variable selection

Gerhard Tutz, Sebastian Petry, G. Tutz, 2012, Stat. Comput..

Regularization and Model Selection with Categorial Effect Modifiers

Gerhard Tutz, Jan Gertheiss, 2010 .

BTLLasso: A Common Framework and Software Package for the Inclusion and Selection of Covariates in Bradley-Terry Models

Gerhard Tutz, Gunther Schauberger, 2019 .

Detection of differential item functioning in Rasch models by boosting techniques.

Gerhard Tutz, Gunther Schauberger, 2016, The British journal of mathematical and statistical psychology.

Analysis of the importance of on-field covariates in the German Bundesliga

Gerhard Tutz, Gunther Schauberger, Andreas H. Groll, 2018 .

Generalized linear random effects models with varying coefficients

Gerhard Tutz, Göran Kauermann, G. Tutz, 2003, Comput. Stat. Data Anal..

Additive mixed models with approximate Dirichlet process mixtures: the EM approach

Gerhard Tutz, Felix Heinzl, G. Tutz, 2016, Stat. Comput..

Exploring Multivariate Data Structures with Local Principal Curves

Gerhard Tutz, Jochen Einbeck, Ludger Evers, 2004, GfKl.

Guest Editorial: Regularisation Methods in Regression and Classification

Gerhard Tutz, 2010, Stat. Comput..

Identification of interaction patterns and classification with applications to microarray data

Gerhard Tutz, Anne-Laure Boulesteix, A. Boulesteix, 2006, Comput. Stat. Data Anal..

Tree-structured modelling of varying coefficients

Gerhard Tutz, Matthias Schmid, Moritz Berger, 2017, Stat. Comput..

Variable selection in general multinomial logit models

Gerhard Tutz, Lorenz Uhlmann, Wolfgang Pößnecker, 2015, Comput. Stat. Data Anal..

Effect Stars for Categorical Response Models

Gerhard Tutz, Gunther Schauberger, G. Tutz, 2012 .

Ordinal Trees and Random Forests: Score-Free Recursive Partitioning and Improved Ensembles

Gerhard Tutz, G. Tutz, 2021, Journal of Classification.

Tree-structured scale effects in binary and ordinal regression

Gerhard Tutz, Moritz Berger, G. Tutz, 2019, Statistics and Computing.

Imputation methods for high-dimensional mixed-type datasets by nearest neighbors

Gerhard Tutz, Shahla Faisal, G. Tutz, 2021, Comput. Biol. Medicine.

Flexible Predictive Distributions from Varying-Thresholds Modelling

Gerhard Tutz, 2021 .

Ordinal regression: A review and a taxonomy of models

Gerhard Tutz, G. Tutz, 2021, WIREs Computational Statistics.

Multivariate ordinal random effects models including subject and group specific response style effects

Gerhard Tutz, Gunther Schauberger, G. Tutz, 2021, Statistical Modelling.

A Rating Scale Mixture Model to Account for the Tendency to Middle and Extreme Categories

Gerhard Tutz, Sabrina Giordano, Roberto Colombi, 2021, Journal of Educational and Behavioral Statistics.

Multiple imputation using nearest neighbor methods

Gerhard Tutz, Shahla Faisal, G. Tutz, 2021, Inf. Sci..

Item Response Thresholds Models

Gerhard Tutz, G. Tutz, 2021, 2106.12784.

A Basic Course in Statistics, 4th edn, G. M. Clarke and D. Cooke, Arnold, 1997. No. of pages:xxiii+672.Price:£19.99.ISBN0340719958

Gerhard Tutz, 2002 .

Shrinkage and variable selection by polytopes

Gerhard Tutz, Sebastian Petry, G. Tutz, 2012 .

Prediction of major international soccer tournaments based on team-specific regularized Poisson regression: An application to the FIFA World Cup 2014

Gerhard Tutz, Gunther Schauberger, G. Tutz, 2015 .

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

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

On association in regression: the coefficient of determination revisited

Gerhard Tutz, G. Tutz, Angelika Van Der Linde, 2008 .

Regularization and Model Selection with Categorial Effect Modifiers

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

Subject-specific modelling of paired comparison data: A lasso-type penalty approach

Gerhard Tutz, Gunther Schauberger, G. Tutz, 2017 .

The fitting of multifunctions : an approach to nonparametric multimodal regression.

Gerhard Tutz, Jochen Einbeck, G. Tutz, 2006 .

Statistical modelling and regression structures : festschrift in honour of Ludwig Fahrmeir

Gerhard Tutz, Ludwig Fahrmeir, Thomas Kneib, 2010 .

Regularization in Cox Frailty Models

Gerhard Tutz, Trevor Hastie, T. Hastie, 2016 .

Tutz , Binder : Generalized additive modelling with implicit variable selection by likelihood based boosting

Gerhard Tutz, Harald Binder, 2004 .

Non-Stationary Conditional Models for Spatial Data Based on Varying Coefficients

Gerhard Tutz, Johannes M. Dreesman, G. Tutz, 2001 .

Discrimination measures for discrete time-to-event predictions

Gerhard Tutz, Matthias Schmid, Thomas Welchowski, 2017 .

Clustering in linear mixed models with approximate Dirichlet process mixtures using EM algorithm

Gerhard Tutz, Felix Heinzl, G. Tutz, 2013 .

Binary and Ordinal Random Effects Models Including Variable Selection

Gerhard Tutz, G. Tutz, Andreas H. Groll, 2010 .

Feature selection guided by structural information

Gerhard Tutz, Wolfgang zu Castell, Martin Slawski, 2010, 1011.2315.

Missing value imputation for gene expression data by tailored nearest neighbors

Gerhard Tutz, Shahla Faisal, G. Tutz, 2017, Statistical applications in genetics and molecular biology.

Regression for Categorical Data

Gerhard Tutz, G. Tutz, 2011 .

Flexible semiparametric mixed models

Gerhard Tutz, Florian Reithinger, 2005 .

Models for Multicategorical Responses: Multivariate Extensions of Generalized Linear Models

Gerhard Tutz, Ludwig Fahrmeir, 2001 .

Combining Quadratic Penalization and Variable Selection via Forward Boosting

Gerhard Tutz, Jan Ulbricht, G. Tutz, 2011 .

Regularized regression for categorical data

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

Local likelihood estimation in varying-coefficient models including additive bias correction

Gerhard Tutz, Göran Kauermann, G. Tutz, 2000 .

Sequential models in categorical regression

Gerhard Tutz, G. Tutz, 1991 .

On the structure of ordered latent trait models

Gerhard Tutz, 2019 .

Penalized Partial Least Squares Based on B-Splines Transformations

Gerhard Tutz, Anne-Laure Boulesteix, Nicole Krämer, 2006 .

State space models

Gerhard Tutz, Ludwig Fahrmeir, 1994 .

Modelling uncertainty and response styles in ordinal data

Gerhard Tutz, Rosaria Simone, G. Tutz, 2018 .

Subjective heterogeneity in response attitude for multivariate ordinal outcomes

Gerhard Tutz, Rosaria Simone, Maria Iannario, 2020 .

Random Forests for Ordinal Response Data: Prediction and Variable Selection

Gerhard Tutz, Anne-Laure Boulesteix, Silke Janitza, 2014 .

Modelling Clustered Heterogeneity: Fixed Effects, Random Effects and Mixtures

Gerhard Tutz, Margret-Ruth Oelker, G. Tutz, 2017 .

Variable Selection and Model Choice in Geoadditive Regression Models

Gerhard Tutz, Torsten Hothorn, Thomas Kneib, 2009, Biometrics.

Competing risks models in discrete time with nominal or ordinal categories of response

Gerhard Tutz, G. Tutz, 1995 .

Hierarchical Models for the Analysis of Likert Scales in Regression and Item Response Analysis

Gerhard Tutz, G. Tutz, 2020, International Statistical Review.

The survival of newly founded firms: a case-study into varying-coefficient models

Gerhard Tutz, Göran Kauermann, Josef Brüderl, 2005 .

Advances in GLIM and Statistical Modelling

Gerhard Tutz, Eric R. Ziegel, Ludwig Fahrmeir, 1992 .

Response Styles in the Partial Credit Model

Gerhard Tutz, Moritz Berger, Gunther Schauberger, 2018, Applied psychological measurement.

On model diagnostics using varying coefficient models

Gerhard Tutz, Göran Kauermann, G. Tutz, 1999 .

Sequential Models for Ordered Responses

Gerhard Tutz, G. Tutz, 1997 .

Fitting generalized additive models: A comparison of methods

Gerhard Tutz, November, Harald Binder, 2008 .

Likelihood-Based Boosting in Binary and Ordinal Random Effects Models

Gerhard Tutz, G. Tutz, Andreas H. Groll, 2013 .

Variable Selection for Generalized Additive Mixed Models by Likelihood-based Boosting

Gerhard Tutz, Andreas Groll, G. Tutz, 2011 .

Testing generalized linear and semiparametric models against smooth alternatives

Gerhard Tutz, Göran Kauermann, 2001 .

Clustering in linear‐mixed models with a group fused lasso penalty

Gerhard Tutz, Felix Heinzl, G. Tutz, 2014, Biometrical journal. Biometrische Zeitschrift.

Aggregating classifiers with ordinal response structure

Gerhard Tutz, Klaus Hechenbichler, G. Tutz, 2005 .

Tree-Structured Clustering in Fixed Effects Models

Gerhard Tutz, Moritz Berger, G. Tutz, 2015, 1512.05169.

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

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

Modelling price paths in on‐line auctions: smoothing sparse and unevenly sampled curves by using semiparametric mixed models

Wolfgang Jank, Gerhard Tutz, Galit Shmueli, 2008 .

Tree-Structured Modelling of Categorical Predictors in Regression

Gerhard Tutz, Moritz Berger, G. Tutz, 2014, 1504.04700.

Nearest neighbor imputation for categorical data by weighting of attributes

Gerhard Tutz, Shahla Faisal, G. Tutz, 2017, Inf. Sci..

Statistical Modelling and Regression Structures

Gerhard Tutz, Thomas Kneib, G. Tutz, 2010 .