This article introduces a new form of empirical distribution function (EDF) called the flipped empirical distribution function (FEDF), to represent univariate data graphically. Because the plot shows the location of individual points, it may be useful when we need to manipulate specific data points as with dynamic graphics. The article introduces several methods to explore multidimensional data using the FEDF. They are called a parallel FEDF, an FEDF scatterplot matrix, and an FEDF starplot. Usefulness of these plots in exploring multidimensional data becomes more prominent when they are implemented with the methods of dynamic graphics such as selecting, deleting, linking, locating, and identifying a group of data points.
The purpose of the Journal of Computational and Graphical Statistics is to improve and extend the use of computational and graphical methods in statistics and data analysis. Established in 1992, this quarterly journal contains cutting-edge research, data, surveys, and more on numerical methods, graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing.
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Journal of Computational and Graphical Statistics
© 1995 American Statistical Association
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