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An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests.
Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with… Expand
Multivariate statistical modelling based on generalized linear models
Introduction * Modelling and Analysis of Cross-sectional Data: A Review of Univariate Generalized Linear Models * Models for Multicategorical Responses: Multivariate Extensions of Generalized Linear… Expand
Generalized additive modeling with implicit variable selection by likelihood-based boosting.
The use of generalized additive models in statistical data analysis suffers from the restriction to few explanatory variables and the problems of selection of smoothing parameters. Generalized… Expand
Variable selection for generalized linear mixed models by L1-penalized estimation
A gradient ascent algorithm is proposed that allows to maximize the penalized log-likelihood of generalized linear mixed models yielding models with reduced complexity. Expand
Sequential item response models with an ordered response
- G. Tutz
- 1 May 1990
A stepwise approach to the construction of latent trait models is outlined. As a special case of the derived general sequential model, a sequential Rasch model is considered. The derivation of the… Expand
Regression for Categorical Data
- G. Tutz
- 21 November 2011
1. Introduction 2. Binary regression: the logit model 3. Generalized linear models 4. Modeling of binary data 5. Alternative binary regression models 6. Regularization and variable selection for… Expand
Dynamic Stochastic Models for Time-Dependent Ordered Paired Comparison Systems
Abstract When paired comparisons are made sequentially over time as for example in chess competitions, it is natural to assume that the underlying abilities do change with time. Previous approaches… Expand
Penalized Regression with Ordinal Predictors
Ordered categorial predictors are a common case in regression modelling. In contrast to the case of ordinal response variables, ordinal predictors have been largely neglected in the literature. In… Expand
Modeling Discrete Time-To-Event Data
This book focuses on statistical methods for the analysis of discrete failure times. Expand