We propose a method for visualization of Generalized Linear Models and describe a variety of interactive and graphical tools for exploratory modeling. This includes graphical model comparison, model diagnostics and variable selection as well as model interpretation, model assessment and the use of experts' knowledge of the underlying dataset.
The use of modern computers not only introduced the benefits of being able to visualize models or to work in an exploratory fashion, it also complicated modeling by being able to compute thousands of models in parallel without yet being able to search model space completely. We will address these problems by graphical (Bayesian) model averaging and graphical visualizations of the model space.
Visualized models are related to statistical models as visualized data such as histograms, bar charts, etc. are related to tables of numbers. We illustrate the interactive and exploratory use of such model visualizations and transfer methods known from exploratory data analysis to the context of model building and model selection.
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