Graphical chain models are a capable tool for analyzing multivariate data. However, their practical use may still be cumbersome in some respect since fitting the model requires the application of an intensive selection strategy based on the calculation of an enormous number of different regressions. In this paper, we present a computer system especially designed for the calculation of graphical chain models which is not only planned to automatically carry out the model search but also to visualize the corresponding graph at each stage of the model fit on request by the user. It additionally allows to modify the graph and the model fit interactively
The first part of the dissertation introduces several new methods for estimating the structure of gr...
We consider the component analysis problem for a regression model with an additive structure. The pr...
Multivariate data are often treated with regression methods on one hand, Geometric Data Analyse me...
Graphical chain models are a capable tool for analyzing multivariate data. However, their practical ...
Graphical chain models are a capable tool for analyzing multivariate data. However, their practical ...
This paper objects to the arising problems due to fitting graphical chain models to multidimensional...
Fitting a graphical chain model to a multivariate data set consists of different steps some of which...
In this paper we extend the concept of graphical models for multivariate data to multivariate time s...
We present two methodologies for Bayesian model choice and averaging in Gaussian directed acyclic gr...
We survey and compare model-based approaches to regression for cross-sectional and longitudinal data...
This thesis explores the use of discriminatively trained deformable contour models (DCMs) for shape-...
With advances in science and information technologies, many scientific fields are able to meet the c...
International audienceGaussian graphical models are widely utilized to infer and visualize networks ...
The first part of the dissertation introduces several new methods for estimating the structure of gr...
We consider the component analysis problem for a regression model with an additive structure. The pr...
Multivariate data are often treated with regression methods on one hand, Geometric Data Analyse me...
Graphical chain models are a capable tool for analyzing multivariate data. However, their practical ...
Graphical chain models are a capable tool for analyzing multivariate data. However, their practical ...
This paper objects to the arising problems due to fitting graphical chain models to multidimensional...
Fitting a graphical chain model to a multivariate data set consists of different steps some of which...
In this paper we extend the concept of graphical models for multivariate data to multivariate time s...
We present two methodologies for Bayesian model choice and averaging in Gaussian directed acyclic gr...
We survey and compare model-based approaches to regression for cross-sectional and longitudinal data...
This thesis explores the use of discriminatively trained deformable contour models (DCMs) for shape-...
With advances in science and information technologies, many scientific fields are able to meet the c...
International audienceGaussian graphical models are widely utilized to infer and visualize networks ...
The first part of the dissertation introduces several new methods for estimating the structure of gr...
We consider the component analysis problem for a regression model with an additive structure. The pr...
Multivariate data are often treated with regression methods on one hand, Geometric Data Analyse me...