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We consider visual methods based on mosaic plots for interpreting and modeling categorical data. Categorical data are most often modeled using loglinear models. For certain loglinear models, mosaic plots have unique shapes that do not depend on the actual data being modeled. These shapes reflect the structure of a model, defined by the presence and absence(More)
Dealing with missing values is inconvenient in many ways. Although every statistician has to admit that the structure of missing values can be very meaningful for the interpretation of data, neither statistical software nor statistical theory can deal with missing values in a convincing way. Interactive Statistical Graphics offer a possibility of getting(More)
There is no native interface to R other than the command line. Since the majority of the users want to have a bit more comfortable interface to R, various, platform dependent GUIs have been developed. They are all different, support different features and are usually insufficient for the expert user. JGR (speak jaguar) is a Java Gui for R. It addresses(More)
1 Introduction 2 The Data ABSTRACT: Categorical data arise in many i n v estigations. Usually, such data will be displayed in contingency tables and analysed using loglinear models and-type-statistics. However, the visualisation of more than three variables is very poor in contingency tables. In the modelling phase, often, imputations based upon prior(More)
Unlike other electrophysiological measurements such as electrocardiography (ECG) and electroencephalography (EEG), the cutaneous measurement of the electrical activity of the stomach (electrogastrography, EGG) is not an established clinical diagnostic procedure. To overcome common problems in acquiring very-low-frequency signals in the presence of large and(More)