Exploring Multidimensional Data with the Flipped Empirical Distribution Function

Abstract

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.

Key Words:

• Dynamic graphics
• FEDF
• FEDF scatterplot matrix
• FEDF starplot
• Parallel FEDF