Thomas Kneib

Details der Publikationsliste

Zeitraum

2003 - 2009

Anzahl

49

Co-Autoren

Additive mixed models with Dirichlet process mixture and P-spline priors (2009)

Heinzl, Felix, Kneib, Thomas, Fahrmeir, Ludwig

Longitudinal data often require a combination of flexible trends and individual-specific random effects. In this paper, we propose a fully Bayesian approach based on Markov chain Monte Carlo...

Identifying Risk Factors for Severe Childhood Malnutrition by Boosting Additive Quantile Regression (2009)

Fenske, Nora, Kneib, Thomas, Hothorn, Torsten

Ordinary linear and generalized linear regression models relate the mean of a response variable to a linear combination of covariate effects and, as a consequence, focus on average properties of the...

On the Behavior of Marginal and Conditional Akaike Information Criteria in Linear Mixed Models (2009)

Greven, Sonja, Kneib, Thomas

The Akaike information criterion (AIC) is often used in regression models to determine the model specifcation most suitable for describing a specifc data generating mechanism. In particular, in...

On the Behavior of Marginal and Conditional Akaike Information Criteria in Linear Mixed Models (2009)

Greven, Sonja, Kneib, Thomas

The Akaike information criterion (AIC) is often used in regression models to determine the model specifcation most suitable for describing a specifc data generating mechanism. In particular, in...

On the Behavior of Marginal and Conditional Akaike Information Criteria in Linear Mixed Models (2009)

Greven, Sonja, Kneib, Thomas

The Akaike information criterion (AIC) is often used in regression models to determine the model specifcation most suitable for describing a specifc data generating mechanism. In particular, in...

On the Behavior of Marginal and Conditional Akaike Information Criteria in Linear Mixed Models (2009)

Greven, Sonja, Kneib, Thomas

The Akaike information criterion (AIC) is often used in regression models to determine the model specifcation most suitable for describing a specifc data generating mechanism. In particular, in...

Variable Selection and Model Choice in Geoadditive Regression Models (2009)

Thomas Kneib, Torsten Hothorn, Gerhard Tutz, Thomas Kneib, Torsten Hothorn, Gerhard Tutz

Model choice and variable selection are issues of major concern in practi-cal regression analyses. We propose a boosting procedure that facilitates both tasks in a class of complex geoadditive...

High-dimensional Structured Additive Regression Models: Bayesian Regularisation, Smoothing and Predictive Performance (2009)

Kneib, Thomas, Konrath, Susanne, Fahrmeir, Ludwig

Data structures in modern applications frequently combine the necessity of flexible regression techniques such as nonlinear and spatial effects with high-dimensional covariate vectors. While...

Spatial Smoothing Techniques for the Assessment of Habitat Suitability (2008)

Thomas Kneib, Jörg Müller, Nationalparkverwaltung Bayerischer Wald, Torsten Hothorn

Precise knowledge about factors influencing the habitat suitability of a certain species forms the basis for the implementation of effective programs to conserve biological diversity. Such knowledge...

Ludwig-Maximilians-University Munich (2008)

Thomas Kneib, Felix Knauer

Investigating habitat selection of animals aims at the detection of preferred and avoided habitat types as well as at the identification of covariates influencing the choice of certain habitat types....

Variable Selection and Model Choice in Structured Survival Models (2008)

Hofner, Benjamin, Hothorn, Torsten, Kneib, Thomas

In many situations, medical applications ask for flexible survival models that allow to extend the classical Cox-model via the inclusion of time-varying and nonparametric effects. These structured...

Bayesian Regularisation in Structured Additive Regression Models for Survival Data (2008)

Konrath, Susanne, Kneib, Thomas, Fahrmeir, Ludwig

During recent years, penalized likelihood approaches have attracted a lot of interest both in the area of semiparametric regression and for the regularization of high-dimensional regression models....

Conditional variable importance for random forests (2008)

Strobl, Carolin, Boulesteix, Anne-Laure, Kneib, Thomas, Augustin, Thomas, Zeileis, Achim

Abstract Background Random forests are becoming increasingly popular in many scientific fields because they can cope with "small n large p" problems, complex interactions and even highly correlated...

Model Choice in Cox-Type Additive Hazard Regression Models with Time-Varying Effects (2008)

Hofner, Benjamin, Kneib, Thomas, Hartl, Wolfgang, Küchenhoff, Helmut

In recent years, flexible hazard regression models based on penalised splines have been developed that allow us to extend the classical Cox-model via the inclusion of time-varying and nonparametric...

Thomas Kneib Survey and Data Survey and Data (2008)

Thomas Kneib, Ludwig Fahrmeir

Spatially correlated categorical time series: A case study in forest health 1. Survey and data 2. Regression models for ordinal responses 3. Geoadditive mixed models 4. Mixed model based inference 5....

Conditional Variable Importance for Random Forests (2008)

Strobl, Carolin, Boulesteix, Anne-Laure, Kneib, Thomas, Augustin, Thomas, Zeileis, Achim

Random forests are becoming increasingly popular in many scientific fields because they can cope with ``small n large p'' problems, complex interactions and even highly correlated predictor...

Locally Adaptive Bayesian P-Splines with a Normal-Exponential-Gamma Prior (2008)

Scheipl, Fabian, Kneib, Thomas

The necessity to replace smoothing approaches with a global amount of smoothing arises in a variety of situations such as effects with highly varying curvature or effects with discontinuities. We...

A General Approach for the Analysis of Habitat Selection (2007)

Kneib, Thomas, Knauer, Felix, Küchenhoff, Helmut

Investigating habitat selection of animals aims at the detection of preferred and avoided habitat types as well as at the identification of covariates influencing the choice of certain habitat types....

Variable Selection and Model Choice in Geoadditive Regression Models (2007)

Kneib, Thomas, Hothorn, Torsten, Tutz, Gerhard

Model choice and variable selection are issues of major concern in practical regression analyses. We propose a boosting procedure that facilitates both tasks in a class of complex geoadditive...

Introduction to the Special Volume on (2007)

Thomas Kneib, Thomas Petzoldt

The third special volume in the "Foometrics in R" series of the Journal of Statistical Software collects a number of contributions describing statistical methodology and corresponding implementations...

Semiparametric Multinomial Logit Models for Analysing Consumer Choice Behaviour. AStA Advances in Statistical Analysis (2007)

Thomas Kneib, Bernhard Baumgartner, Winfried J. Steiner

The multinomial logit model (MNL) is one of the most frequently used statistical models in marketing applications. It allows to relate an unordered categorical response variable, for example...

Mixed model based inference in structured additive regression (2006)

Kneib, Thomas

Due to the increasing availability of spatial or spatio-temporal regression data, models that allow to incorporate the special structure of such data sets in an appropriate way are highly desired in...

Mixed model based inference in structured additive regression (2006)

Kneib, Thomas

Due to the increasing availability of spatial or spatio-temporal regression data, models that allow to incorporate the special structure of such data sets in an appropriate way are highly desired in...

Spatial Smoothing Techniques for the Assessment of Habitat Suitability (2006)

Kneib, Thomas, Müller, Jörg, Hothorn, Torsten

Precise knowledge about factors influencing the habitat suitability of a certain species forms the basis for the implementation of effective programs to conserve biological diversity. Such knowledge...

Semiparametric Multinomial Logit Models for Analysing Consumer Choice Behaviour (2006)

Kneib, Thomas, Baumgartner, Bernhard, Steiner, Winfried J.

The multinomial logit model (MNL) is one of the most frequently used statistical models in marketing applications. It allows to relate an unordered categorical response variable, for example...

Bayesian Semiparametric Multi-State Models (2006)

Kneib, Thomas, Hennerfeind, Andrea

Multi-state models provide a unified framework for the description of the evolution of discrete phenomena in continuous time. One particular example are Markov processes which can be characterised by...

Propriety of Posteriors in Structured Additive Regression Models: Theory and Empirical Evidence (2006)

Fahrmeir, Ludwig, Kneib, Thomas

Structured additive regression comprises many semiparametric regression models such as generalized additive (mixed) models, geoadditive models, and hazard regression models within a unified...

Supplement to "Structured additive regression for categorical space-time data: A mixed model approach" (2005)

Kneib, Thomas, Fahrmeir, Ludwig

This technical report acts as a supplement to the paper "Structured additive regression for categorical space-time data: A mixed model approach" (Kneib and Fahrmeir, Biometrics, 2005, to appear)....

Geoadditive hazard regression for interval censored survival times (2005)

Kneib, Thomas

The Cox proportional hazards model is the most commonly used method when analyzing the impact of covariates on continuous survival times. In its classical form, the Cox model was introduced in the...

Bayesian semiparametric regression based on MCMC techniques: A tutorial (2005)

Thomas Kneib, Stefan Lang, Andreas Brezger

This tutorial demonstrates the usage of BayesX for analysing Bayesian semiparametric regression models based on MCMC techniques. As an example we consider data on undernutrition of children in...

Structured additive regression for multicategorical space-time data: A mixed model approach (2004)

Kneib, Thomas, Fahrmeir, Ludwig

In many practical situations, simple regression models suffer from the fact that the dependence of responses on covariates can not be sufficiently described by a purely parametric predictor. For...

A mixed model approach for structured hazard regression (2004)

Kneib, Thomas, Fahrmeir, Ludwig

The classical Cox proportional hazards model is a benchmark approach to analyze continuous survival times in the presence of covariate information. In a number of applications, there is a need to...

Structured additive regression for multicategorical space-time data: A mixed model approach (2004)

Thomas Kneib, Ludwig Fahrmeir

In many practical situations, simple regression models suffer from the fact that the dependence of responses on covariates can not be sufficiently described by a purely parametric predictor. For...

Bayesian semiparametric regression based on MCMC techniques: A tutorial (2004)

Thomas Kneib, Stefan Lang, Andreas Brezger

This tutorial demonstrates the usage of BayesX for analysing Bayesian semiparametric regression models based on MCMC techniques. As an example we consider data on undernutrition of children in...

Penalized structured additive regression for space-time data: a Bayesian perspective (2004)

Ludwig Fahrmeir, Thomas Kneib, Stefan Lang

We propose extensions of penalized spline generalized additive models for analyzing space-time regression data and study them from a Bayesian perspective. Non-linear effects of continuous covariates...

Contents (2004)

Thomas Kneib, Stefan Lang, Andreas Brezger

This tutorial demonstrates the usage of BayesX for analysing Bayesian semiparametric regression models based on mixed model methodology. As an example we consider data on undernutrition of children...

Penalized additive regression for space-time data: a Bayesian perspective (2003)

Fahrmeir, Ludwig, Kneib, Thomas, Lang, S.

We propose extensions of penalized spline generalized additive models for analysing space-time regression data and study them from a Bayesian perspective. Non-linear effects of continuous covariates...

BayesX: Analysing Bayesian structured additive regression models (2003)

Brezger, Andreas, Kneib, Thomas, Lang, S.

There has been much recent interest in Bayesian inference for generalized additive and related models. The increasing popularity of Bayesian methods for these and other model classes is mainly caused...

Penalized structured additive regression for space-time data: a Bayesian perspective (2003)

Ludwig Fahrmeir, Thomas Kneib, Stefan Lang

We propose extensions of penalized spline generalized additive models for analysing space-time regression data and study them from a Bayesian perspective. Non-linear effects of continuous covariates...

Semiparametric multinomial logit models for analysing consumer choice behaviour

Thomas Kneib, Bernhard Baumgartner, Winfried Steiner

Brand choice, Conditional logit model, Mixed models, Multinomial logit model, Penalised splines, Proper scoring rules, Semiparametric regression ,

A Mixed Model Approach for Geoadditive Hazard Regression

THOMAS KNEIB, LUDWIG FAHRMEIR

Mixed model based approaches for semiparametric regression have gained much interest in recent years, both in theory and application. They provide a unified and modular framework for penalized...

BayesX: Analyzing Bayesian Structural Additive Regression Models

Andreas Brezger, Thomas Kneib, Stefan Lang

There has been much recent interest in Bayesian inference for generalized additive and related models. The increasing popularity of Bayesian methods for these and other model classes is mainly caused...

Introduction to the Special Volume on "Ecology and Ecological Modeling in R"

Thomas Kneib, Thomas Petzoldt

The third special volume in the “Foometrics in R†series of the Journal of Statistical Software collects a number of contributions describing statistical methodology and corresponding...

Simultaneous Confidence Bands for Penalized Spline Estimators

Tatyana Krivobokova, Thomas Kneib, Gerda Claeskens

In this paper we construct simultaneous confidence bands for a smooth curve using penalized spline estimators. We consider three types of estimation methods: (i) as a standard (fixed effect)...

Locally adaptive Bayesian P-splines with a Normal-Exponential-Gamma prior

Scheipl, Fabian, Kneib, Thomas

An implementation of locally adaptive penalized spline smoothing using a class of heavy-tailed shrinkage priors for the estimation of functional forms with highly varying curvature or discontinuities...