1 Curriculum Vitae - Georg-August-Universität Göttingen

28 5 Software5 SoftwareBayesXBayesX is a stand-alone software implemented in C++ and Java that provides functionalityfor estimating structured additive regression models in a variety of situations. Jointlywith Andreas Brezger, Christiane Belitz and Stefan Lang, I am one of the main developersof BayesX. Seven further colleagues have contributed to the BayesX project.In the current release, the main capabilities of BayesX are as follows:• Command-line based execution of commands in a syntax that is closely related tothe one of Stata.• Functions for manipulating data and for descriptive analyses.• Functions for handling and manipulating geographical information and spatial data.• Functions for visualizing data and estimation results, in particular for drawing andcolouring geographical maps.• Estimation of structured additive regression models based on mixed model methodology(remlreg objects) or Markov chain Monte Carlo simulations (bayesreg objects).BayesX supports univariate exponential family regression, multicategorical responses,continuous time survival time regression and multi-state models.• A similar class of models can be estimated based on stepwise procedures (stepwiseregobjects).• Estimation of graphical models based on directed acyclic graphs (DAGs).My responsibilities in the development of BayesX so far have been:• The implementation of all mixed model based inferential procedures.• The implementation of some MCMC-based extensions.• The implementation of a matrix class for sparse matrix computations and efficientrandom number generation.• The implementation of the graphical user interface.In the future, a connection to R will be considered to ensure better perception of thesoftware in the statistical community. A first step towards this goal is the R-packageBayesX that provides functionality for visualising estimation results and for manipulatinggeographical information.BayesX is available free of charge from http://www.stat.uni-muenchen.de/~bayesx/.R-package mboostAs an add-on package to the statistical software R, mboost implements boosting approachesfor variable selection and model choice. In collaboration with Torsten Hothorn