Regression Methods via ARC

ARC is a framework for the exploration and graphical display of regression model structure and diagnostics. Focus is placed on understanding the conditional mean and variance functions, model structural dimension, nonlinearity, curvature, smoothing, transformation and model assessment. The uniqueness of the user interface was designed to allow interactive choice during all phases of use. Graphical regression, brushing and slicing allows for additional insights related to model building. In addition, extensions of these topics to the Generalized Linear Model framework allows for a larger class of models such as; binomial, logistic, poisson and gamma families.