Allan R. Wilks

The new S language: a programming environment for data analysis and graphics

This book provides documentation for a new version of the S system released in 1988. The New S Language enhances the features that have made S popular: interactive computing, flexible graphics, data management and a large collection of functions. The New S language features make possible new applications and higher-level programming, including a single unified language, user-defined functions as first-class objects, symbolic computations, more accurate numerical calculations and a new approach to graphics. S now provides direct interfaces to the powerful tool of the UNIX operating system and to algorithms implemented in Fortran and C.

Visualizing network data

Networks are critical to modern society, and a thorough understanding of how they behave is crucial to their efficient operation. Fortunately, data on networks is plentiful; by visualizing this data, it is possible to greatly improve our understanding. Our focus is on visualizing the data associated with a network and not on simply visualizing the structure of the network itself. We begin with three static network displays; two of these use geographical relationships, while the third is a matrix arrangement that gives equal emphasis to all network links. Static displays can be swamped with large amounts of data; hence we introduce direct manipulation techniques that permit the graphs to continue to reveal relationships in the context of much more data. In effect, the static displays are parameterized so that interesting views may easily be discovered interactively. The software to carry out this network visualization is called SeeNet. >

Contour tracing by piecewise linear approximations

We present a method for tracing a curve that is represented as the contour of a function in Euclidean space of any dimension. The method proceeds locally by following the intersections of the contour with the facets of a triangulation of space. The algorithm does not fail in the presence of high curvature of the contour; it accumulates essentially no round-off error and has a well-defined integer test for detecting a loop. In developing the algorithm, we explore the nature of a particular class of triangulations of Euclidean space, namely, those generated by reflections.

Analysis of Data from the Places Rated Almanac

Abstract This article presents an analysis of data from the 1985 edition of the Places Rated Almanac by Boyer and Savageau. The data consist of nine composite variables constructed for 329 metropolitan areas of the United States. We present alternatives to the ranking method used in the original source and provide graphical displays to aid the reader in understanding the data.

Fraud Detection in Telecommunications: History and Lessons Learned

Fraud detection is an increasingly important and difficult task in today’s technological environment. As consumers are putting more of their personal information online and transacting much more business over computers, the potential for losses from fraud is in the billions of dollars, not to mention the damage done by identity theft. This paper reviews the history of fraud detection at AT&T, one of the first companies to address fraud in a systematic way to protect its revenue stream. We discuss some of the major fraud schemes and the techniques used to address them, leading to generic conclusions about fraud detection. Specifically, we advocate the use of simple, understandable models, heavy use of visualization, and a flexible environment and emphasize the importance of data management and the need to keep humans in the loop.

Gray codes for reflection groups

LetG be a finite group generated by reflections. It is shown that the elements ofG can be arranged in a cycle (a “Gray code”) such that each element is obtained from the previous one by applying one of the generators. The case G =A1n yields a conventional binary Gray code. These generalized Gray codes provide an efficient way to run through the elements of any finite reflection group.

Dynamic graphics for network visualization

The authors describe several dynamic graphics tools for visualizing network data involving statistics associated with the nodes or links in a network. The authors suggest a number of ideas for the static display of network data, while motivating the need for interaction through dynamic graphics. A brief discussion of dynamic graphics in general is presented. The authors specialize this to the case of network data. An example is presented.<<ETX>>