Aydemir, Biller: Kernel smoothing of Aalen’s linear regression model (2008)
Kernel smoothing of Aalen's linear regression model
Clemens Biller, Ludwig Fahrmeir, Clemens Biller, Ludwig Fahrmeir
Bayesian varying-coefficient models using adaptive regression splines
Discrete Duration Models combining Dynamic and Random Effects (2007)
this paper we propose the DGLMM for discrete duration and competing risks data as a model that includes both dynamic time--varying effects and unit--specific random effects. Based on the results of...
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...
Bayesianische Ansätze zur nonparametrischen Regression / (2000)
Zugl.: München, Universiẗat, Diss., 2000.
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...
Adaptive Bayesian regression splines in semiparametric generalized linear models (2000)
This paper presents a fully Bayesian approach to regression splines with automatic knot selection in generalized semiparametric models for fundamentally non{Gaussian responses. In a basis function...
Adaptive Bayesian Regression Splines in Semiparametric Generalized Linear Models (1998)
This paper presents a fully Bayesian approach to regression splines with automatic knot selection in generalized semiparametric models for fundamentally non-Gaussian responses. In a basis function...
Adaptive Bayesian Regression Splines in Semiparametric Generalized Linear Models (1998)
This paper presents a fully Bayesian approach to regression splines with automatic knot selection in generalized semiparametric models for fundamentally non--Gaussian responses. In a basis function...
Posterior mode estimation in dynamic generalized linear mixed models. (REVISED, June 2000) (1997)
Dynamic generalized linear mixed models for longitudinal data combine the generalized linear mixed model and the dynamic generalized linear model dealing with the case that both unit- and...
Discrete Duration Models combining Dynamic and Random Effects. (REVISED, February 2000) (1997)
Survival data may include two different sources of variation, namely variation over time and variation over units. If both of these variations are present, neglecting one of them can cause serious...
Kernel smoothing of Aalen's linear regression model (1997)
Aydemir, Sibel, Biller, Clemens
The linear regression model by Aalen for failure time analysis allows the inclusion of time-dependent covariates as well as the variation of covariate effects over time. For estimation Aalen...
Posterior Mode Estimation in Dynamic Generalized Linear Mixed Models (1997)
this paper we consider an extended version of the DGLMM by additionally adding the fixed effect ff to the linear predictor of Knorr-Held (1995), thus getting the linear predictor
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...