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...
Geoadditive Latent Variable Modelling of Count Data on Multiple Sexual Partnering in Nigeria (2009)
Adebayo, Samson B., Fahrmeir, Ludwig, Seiler, Christian
The 2005 National HIV/AIDS and Reproductive Health Survey in Nigeria provides evidence that multiple sexual partnering increases the risk of contracting HIV and other sexually transmitted diseases....
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...
Ludwig Fahrmeir, Christian Gieger, Christian Heumann
This paper discusses marginal regression for repeated ordinal measurements that are isotonic over time. Such data are often observed in longitudinal studies on healing processes where, due to...
Fenske, Nora, Fahrmeir, Ludwig, Rzehak, Peter, Höhle, Michael
This article compares and discusses three different statistical methods for investigating risk factors for overweight and obesity in early childhood by means of the LISA study, a recent German birth...
Alternative regression models to assess increase in childhood BMI (2008)
Beyerlein, Andreas, Fahrmeir, Ludwig, Mansmann, Ulrich, Toschke, André M
Abstract Background Body mass index (BMI) data usually have skewed distributions, for which common statistical modeling approaches such as simple linear or logistic regression have limitations....
Clemens Biller, Ludwig Fahrmeir, Clemens Biller, Ludwig Fahrmeir
Bayesian varying-coefficient models using adaptive regression splines
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....
Thomas Kneib Survey and Data Survey and Data (2008)
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....
with contributions by supported by (2008)
Christiane Belitz, Ludwig Fahrmeir, Leo Held, Andrea Hennerfeind, German Science Foundation, Manuela Hummel, ...
developed at developed by
Geoadditive Latent Variable Modelling of Child Morbidity and Malnutrition in Nigeria (2008)
Fahrmeir, Ludwig, Khatab, Khaled
Investigating the impact of important risk factors and geographical location on child morbidity and malnutrition is of high relevance for developing countries. Previous research has usually carried...
Khatab, Khaled, Fahrmeir, Ludwig
Childhood diseases are a major cause of death of children in the developing world. In developing countries a quarter of infant and childhood mortality is related to childhood disease particularly to...
A Latent Variable Probit Model for Multivariate Ordered Categorical Responses (2007)
Marion Nikele, Ludwig Fahrmeir
This paper presents a fully Bayesian approach via Gibbs sampling for MIMIC models with ordered categorical outcomes. The method is of particular interest for moderate or medium sample size data...
State Space Models: A Brief History and Some Recent Developments (2007)
Introduction State space models, also termed dynamic models, relate observations y t ; t = 1; 2;:::, on a response variable Y to unobserved "states" or "parameters" # t ,...
Discrete Failure Time Models (2007)
Introduction Most methods for analyzing failure time or event history data are based on time as a continuously measured variate. A basic assumption for large parts of theory is that failure times are...
In this paper, we analyze unemployment duration in Germany with o#cial data from the German Federal Employment O#ce for the years 1980-1995. Conventional hazard rate models for leaving unemployment...
Bayesian Geoadditive Seemingly Unrelated Regression (2007)
Stefan Lang, Samson B. Adebayo, Ludwig Fahrmeir, Winfried J. Steiner
Parametric seemingly unrelated (SUR) models are... In this paper, we develop a Bayesian semiparametric SUR model, where the usual linear predictors are replaced by more flexible additive predictors...
A Bayesian semiparametric latent variable model for mixed responses (2006)
Fahrmeir, Ludwig, Raach, Alexander
In this article we introduce a latent variable model (LVM) for mixed ordinal and continuous responses, where covariate effects on the continuous latent variables are modelled through a flexible...
A geoadditive Bayesian latent variable model for Poisson indicators (2006)
Fahrmeir, Ludwig, Steinert, Sven
We introduce a new latent variable model with count variable indicators, where usual linear parametric effects of covariates, nonparametric effects of continuous covariates and spatial effects on the...
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...
Geoadditive survival models (2005)
Hennerfeind, Andrea, Brezger, Andreas, Fahrmeir, Ludwig
Survival data often contain small-area geographical or spatial information, such as the residence of individuals. In many cases the impact of such spatial effects on hazard rates is of considerable...
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 Survival Models: A Supplement (2005)
Hennerfeind, Andrea, Brezger, Andreas, Fahrmeir, Ludwig
This technical report supplements the paper Geoadditive Survival Models (Hennerfeind, Brezger and Fahrmeir, 2005, Revised for JASA). In particular, we describe the simulation study of this paper in...
Space-Varying Coefficient Models for Brain Imaging (2005)
Heim, Susanne, Fahrmeir, Ludwig, Eilers, Paul H. C., Marx, Brian D.
The methodological development and the application in this paper originate from diffusion tensor imaging (DTI), a powerful nuclear magnetic resonance technique enabling diagnosis and monitoring of...
Adaptive Gaussian Markov Random Fields with Applications in Human Brain Mapping (2005)
Brezger, Andreas, Fahrmeir, Ludwig, Hennerfeind, Andrea
Functional magnetic resonance imaging (fMRI) has become the standard technology in human brain mapping. Analyses of the massive spatio-temporal fMRI data sets often focus on parametric or...
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)
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...
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...
Bayesian P-Splines in Structured Additive Regression Models (2004)
Andreas Brezger, Andreas Brezger, Andreas Brezger, Erstgutachter Prof, Dr. Ludwig Fahrmeir, Zweitgutachter Prof, ...
vor der geraden Linie.
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...
Assessing Brain Activity through Spatial Bayesian Variable Selection (2003)
Smith, Michael, Pütz, Benno, Auer, Dorothee P., Fahrmeir, Ludwig
Statistical parametric mapping (SPM), relying on the general linear model and classical hypothesis testing, is a benchmark tool for assessing human brain activity using data from fMRI experiments....
Bayesian mapping of brain regions using compound Markov random field priors (2003)
Fahrmeir, Ludwig, Gössl, Christoff, Hennerfeind, Andrea
Human brain mapping, i.e. the detection of functional regions and their connections, has experienced enormous progress through the use of functional magnetic resonance imaging (fMRI). The massive...
Geoadditive survival models (2003)
Hennerfeind, Andrea, Brezger, Andreas, Fahrmeir, Ludwig
Survival data often contain geographical or spatial information, such as the residence of individuals. We propose geoadditive survival models for analyzing spatial effects jointly with possibly...
Structured count data regression (2003)
Overdispersion in count data regression is often caused by neglection or inappropriate modelling of individual heterogeneity, temporal or spatial correlation, and nonlinear covariate effects. In this...
Gehrmann, U., Hellriegel, B., Neiss, A., Fahrmeir, Ludwig
The course of multiple sclerosis (MS) is generally difficult to predict. This is due to the great inter-individual variability with respect to symptoms and disability status. An important prognostic...
Nonparametric Bayesian hazard rate models based on penalized splines (2003)
Fahrmeir, Ludwig, Hennerfeind, Andrea
Extensions of the traditional Cox proportional hazard model, concerning the following features are often desirable in applications: Simultaneous nonparametric estimation of baseline hazard and usual...
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...
Geo-additive models of Childhood Undernutrition in three Sub-Saharan African Countries (2002)
Kandala, N. B., Fahrmeir, Ludwig, Klasen, S.
We investigate the geographical and socioeconomic determinants of childhood undernutrition in Malawi, Tanzania and Zambia, three neighboring countries in Southern Africa using the 1992 Demographic...
Dynamic Modelling of Child Mortality in Developing Countries: Application for Zambia (2002)
Berger, U., Fahrmeir, Ludwig, Klasen, S.
In this paper, we analyse the causes of under five mortality in Zambia, with a particular emphasis on assessing possible time-variations in the effects of covariates, i.e. whether the effects of...
Bayesian Geoadditive Seemingly Unrelated Regression (2002)
Lang, Stefan, Adebayo, Samson B., Fahrmeir, Ludwig, Steiner, Winfried J.
Parametric seemingly unrelated regression (SUR) models are a common tool for multivariate regression analysis when error variables are reasonably correlated, so that separate univariate analysis may...
Analyzing Child Mortality in Nigeria with Geoadditive Survival Models (2002)
Adebayo, Samson B., Fahrmeir, Ludwig
Child mortality reflects a country's level of socio-economic development and quality of life. In developing countries, mortality rates are not only influenced by socio-economic, demographic and...
L.: Bayesian space-time analysis of health insurance data (2002)
Stefan Lang, Petra Kragler, Gerhard Haybach, Ludwig Fahrmeir
Generalized linear models (GLMs) and semiparametric extensions provide a exible framework for analyzing the claims process in non-life insurance. Currently, most applications are still based on...
Bayesian generalized additive mixed models. A simulation study (2001)
Generalized additive mixed models extend the common parametric predictor of generalized linear models by adding unknown smooth functions of different types of covariates as well as random effects....
Bayesian space-time analysis of health insurance data (2001)
Lang, S., Kragler, P., Haybach, G., Fahrmeir, Ludwig
Generalized linear models (GLMs) and semiparametric extensions provide a flexible framework for analyzing the claims process in non-life insurance. Currently, most applications are still based on...
Kandala, N. B., Lang, S., Klasen, S., Fahrmeir, Ludwig
We estimate semiparametric regression models of chronic undernutrition (stunting) using the 1992 Demographic and Health Surveys (DHS) from Tanzania and Zambia. We focus particularly on the influence...
Function estimation with locally adaptive dynamic models (2001)
Lang, S., Fronk, Eva-Maria, Fahrmeir, Ludwig
We present a nonparametric Bayesian method for fitting unsmooth and highly oscillating functions, which is based on a locally adaptive hierarchical extension of standard dynamic or state space...
Semiparametric Bayesian Time-Space Analysis of Unemployment Duration (2001)
In this paper, we analyze unemployment duration in Germany with official data from the German Federal Employment Office for the years 1980-1995. Conven-tional hazard rate models for leaving...
Bayesian semiparametric regression analysis of multicategorical time-space data (2001)
We present a unified semiparametric Bayesian approach based on Markov random field priors for analyzing the dependence of multicategorical response variables on time, space and further covariates....
Bayesian Generalized Additive Mixed Models. A Simulation Study (2001)
Generalized additive mixed models extend the common parametric predictor of generalized linear models by adding unknown smooth functions of dierent types of covariates as well as random eects. From a...
Bayesian inference for generalized additive mixed models based on Markov random field priors (2001)
Summary. Most regression problems in practice require ¯exible semiparametric forms of the predictor for modelling the dependence of responses on covariates. Moreover, it is often necessary to add...
Bayesian spatio-temporal inference in functional magnetic resonance imaging (2000)
Gössl, Christoff, Auer, Dorothee P., Fahrmeir, Ludwig
Mapping of the human brain by means of functional magnetic resonance imaging (fMRI) is an emerging field in medical sciences. Current techniques to detect activated areas of the brain mostly proceed...
Bayesian Semiparametric Regression Analysis of Multicategorical Time-Space Data (2000)
We present a unified semiparametric Bayesian approach based on Markov random field priors for analyzing the dependence of multicategorical response variables on time, space and further covariates....
Bayesian Varying-coefficient Models using Adaptive Regression Splines (2000)
Biller, Clemens, Fahrmeir, Ludwig
Varying-coefficient models provide a flexible framework for semi- and nonparametric generalized regression analysis. We present a fully Bayesian B-spline basis function approach with adaptive knot...
Semiparametric Bayesian Time-Space Analysis of Unemployment Duration (2000)
Fahrmeir, Ludwig, Lang, S., Wolff, J., Bender, S.
In this paper, we analyze unemployment duration in Germany with official data from the German Federal Employment Office for the years 1980-1995. Conventional hazard rate models for leaving...
Dynamic and semiparametric models (2000)
Ludwig Fahrmeir, Leonhard Knorr--held
This chapter surveys dynamic or state space models and their relationship to non-- and semiparametric models that are based on the roughness penalty approach. We focus on recent advances in dynamic...
Bayesian Semiparametric Regression Analysis of Multicategorical Time-Space Data (2000)
this paper, we consider multicategorical time-space data, where the spatial location or site s on a spatial array f1; : : : ; s; : : : ; Sg is given for each unit as an additional 1
Bayesian Varying-coefficient Models using Adaptive Regression Splines (2000)
Clemens Biller, Ludwig Fahrmeir
Varying{coecient models provide a exible framework for semi{ and nonparametric generalized regression analysis. We present a fully Bayesian B{spline basis function approach with adaptive knot...
Bayesian Inference for Generalized Additive Mixed Models Based on Markov Random Field Priors (2000)
Most regression problems in practice require flexible semiparametric forms of the predictor for modelling the dependence of responses on covariates. Moreover, it is often necessary to add random...
A latent variable probit model for multivariate ordered categorical responses (1999)
This paper presents a fully Bayesian approach via Gibbs sampling for MIMIC models with ordered categorical outcomes. The method is of particular interest for moderate or medium sample size data...
Bayesian Inference for Generalized Additive Mixed Models Based on Markov Random Field Priors (1999)
Most regression problems in practice require flexible semiparametric forms of the predictor for modelling the dependence of responses on covariates. Moreover, it is often necessary to add random...
An Application of Isotonic Longitudinal Marginal Regression to Monitoring the Healing Process (1999)
Ludwig Fahrmeir, Christian Gieger, Christian Heumann
This paper discusses marginal regression for repeated ordinal measurements that are isotonic over time. Such data are often observed in longitudinal studies on healing processes where, due to...
Bayesian Inference for Generalized Additive Regression based on Dynamic Models (1999)
We present a general approach for Bayesian inference via Markov chain Monte Carlo (MCMC) simulation in generalized additive, semiparametric and mixed models. It is particularly appropriate for...
Penalized likelihood smoothing in robust state space models (1998)
Fahrmeir, Ludwig, Künstler, R.
In likelihood-based approaches to robustify state space models, Gaussian error distributions are replaced by non-normal alternatives with heavier tails. Robustified observation models are appropriate...
Bayesian Inference for Generalized Additive Regression based on Dynamic Models (1998)
We present a general approach for Bayesian inference via Markov chain Monte Carlo (MCMC) simulation in generalized additive, semiparametric and mixed models. It is particularly appropriate for...
Function estimation with locally adaptive dynamic models (1998)
Fronk, Eva-Maria, Fahrmeir, Ludwig
We present a nonparametric Bayesian method for fitting unsmooth functions which is based on a locally adaptive hierarchical extension of standard dynamic or state space models. The main idea is to...
Gössl, Christoff, Auer, Dorothee P., Fahrmeir, Ludwig
Most statistical methods for assessing activated voxels in fMRI experiments are based on correlation or regression analysis. In this context the main assumptions are that the baseline can be...
Recent Advances in Semiparametric Bayesian Function Estimation (1998)
Common nonparametric curve fitting methods such as spline smoothing, local polynomial regression and basis function approaches are now well developed and widely applied. More recently, Bayesian...
Recent advances in semiparametric Bayesian function estimation. Discussion Paper 137 (1998)
Abstract: Common nonparametric curve tting methods such as spline smoothing, local polynomial regression and basis function approaches are now well developed and widely applied. More recently,...
Function Estimation with Locally Adaptive Dynamic Models (1998)
We present a nonparametric Bayesian method for fitting unsmooth and highly oscillating functions, which is based on a locally adaptive hierarchical extension of standard dynamic or state space...
Recent Advances in Semiparametric Bayesian Function Estimation (1998)
: Common nonparametric curve fitting methods such as spline smoothing, local polynomial regression and basis function approaches are now well developed and widely applied. More recently, Bayesian...
Function Estimation With Locally Adaptive Dynamic Models (1998)
Eva-Maria Fronk, Ludwig Fahrmeir
We present a nonparametric Bayesian method for fitting unsmooth functions which is based on a locally adaptive hierarchical extension of standard dynamic or state space models. The main idea is to...
Penalized Likelihood Smoothing in Robust State Space Models (1998)
Ludwig Fahrmeir, Rita Künstler, Seminar Fur Statistik
In likelihood-based approaches to robustify state space models, Gaussian error distributions are replaced by non-normal alternatives with heavier tails. Robustified observation models are appropriate...
A nonparametric multiplicative hazard model for event history analysis (1998)
FAHRMEIR, LUDWIG, KLINGER, ARTUR
A major issue in exploring and analysing complex life history data with multiple states and recurrent events is the development and availability of flexible models and methods that allow the...
Dynamic and semiparametric models (1997)
Fahrmeir, Ludwig, Knorr-Held, Leonhard
This paper surveys dynamic or state space models and their relationship to non- and semiparametric models that are based on the roughness penalty approach. We focus on recent advances in dynamic...
Fahrmeir, Ludwig, Klinger, Artur
A major issue in exploring and analyzing complex life history data with multiple states and recurrent events is the development and availability of flexible models and methods that allow to discover...
An application of isotonic longitudinal marginal regression to monitoring the healing process (1997)
Fahrmeir, Ludwig, Gieger, Christian, Heumann, Christian
This paper discusses marginal regression for repeated ordinal measurements that are isotonic over time. Such data are often observed in longitudinal studies on healing processes where, due to...
Discrete failure time models (1997)
Most methods for analyzing failure time or event history data are based on time as a continuously measured variate. A basic assumption for large parts of theory is that failure times are untied, see...
Ludwig Fahrmeir, Stefan Wagenpfeil
. Dynamic regression or state space models provide a flexible framework for analyzing non-Gaussian time series and longitudinal data, covering for example models for discrete longitudinal...
Dynamic Discrete-Time Duration Models (1997)
Ludwig Fahrmeir, Leonhard Knorr-Held
Discrete--time grouped duration data, with one or multiple types of terminating events, are often observed in social sciences or economics. In this paper we suggest and discuss dynamic models for...
Dynamic discrete-time duration models. (REVISED) (1996)
Fahrmeir, Ludwig, Knorr-Held, Leonhard
Discrete-time grouped duration data, with one or multiple types of terminating events, are often observed in social sciences or economics. In this paper we suggest and discuss dynamic models for...
Bayesian spline-type smoothing in generalized regression models (1996)
Biller, Clemens, Fahrmeir, Ludwig
Spline smoothing in non- or semiparametric regression models is usually based on the roughness penalty approach. For regression with normal errors, the spline smoother also has a Bayesian...
Ludwig Fahrmeir, Stefan Wagenpfeil
this paper we propose state space or dynamic models as a flexible technique, which makes simultaneous modelling and smooth estimation of hazard functions and covariate effects possible. The...
Regression Analysis of Forest Damage By Marginal Models for Correlated Ordinal Responses (1996)
Ludwig Fahrmeir, Lisa Pritscher
Studies on forest damage can generally not be carried out by common regression models, mainly for two reasons: Firstly, the response variable, damage state of trees, is usually observed in ordered...
Additive, Dynamic and Multiplicative Regression (1995)
Fahrmeir, Ludwig, Gieger, Christian, Klinger, Artur
We survey and compare model-based approaches to regression for cross-sectional and longitudinal data which extend the classical parametric linear model for Gaussian responses in several aspects and...
Fahrmeir, Ludwig, Wagenpfeil, Stefan
Dynamic regression or state space models provide a flexible framework for analyzing non-Gaussian time series and longitudinal data, covering for example models for discrete longitudinal observations....
Fahrmeir, Ludwig, Wagenpfeil, Stefan
State space or dynamic approaches to discrete or grouped duration data with competing risks or multiple terminating events allow simultaneous modelling and smooth estimation of hazard functions and...
Regression analysis of forest damage by marginal models for correlated ordinal responses (1995)
Fahrmeir, Ludwig, Pritscher, L.
Studies on forest damage can generally not be carried out by common regression models, mainly for two reasons: Firstly, the response variable, damage state of trees, is usually observed in ordered...
A nonparametric multiplicative hazard model for event history analysis (1995)
Fahrmeir, Ludwig, Klinger, Artur
A major issue in exploring and analyzing life history data with multiple states and events is the development and availability of flexible methods that allow simultaneous incorporation and estimation...
Additive, Dynamic and Multiplicative Regression (1995)
Ludwig Fahrmeir, Christian Gieger, Artur Klinger
this paper we will focus on penalized least squares and likelihood methods as a unifying modelling and estimation approach. From this point of view, the smooth functions f j () are unknown, but...
A Nonparametric Multiplicative Hazard Model for Event History Analysis (1995)
Ludwig Fahrmeir, Artur Klinger
this paper we consider a nonparametric multiplicative hazard model that takes into account these aspects. Embedded in the counting process approach, estimation is based on penalized likelihoods and...
Approximation und Schätzung stochastischer Systeme. (1977)
München, Techn. Univ., Habil.-Schr., 1977.
Thesis (doctoral)--Technische Universität München, 1972.
A Mixed Model Approach for Geoadditive Hazard Regression
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...
Alternative regression models to assess increase in childhood BMI
Beyerlein, Andreas, Fahrmeir, Ludwig, Mansmann, Ulrich, Toschke, André M
A Bayesian Semiparametric Latent Variable Model for Mixed Responses
Ludwig Fahrmeir, Alexander Raach
latent variable models, mixed responses, penalized splines, spatial effects, MCMC,
Bayesian Semiparametric Regression Analysis of Multicategorical Time-Space Data
Categorical time-space data, forest damage, latent utility models, Markov random fields, MCMC, probit models, semiparametric Bayesian inference, unemployment,
Some asymptotic results on generalized penalized spline smoothing
Göran Kauermann, Tatyana Krivobokova, Ludwig Fahrmeir
The paper discusses asymptotic properties of penalized spline smoothing if the spline basis increases with the sample size. The proof is provided in a generalized smoothing model allowing for...