Computing and Graphics in Statistics available in Hardcover
- Pub. Date:
- Springer New York
This IMA Volume in Mathematics and its Applications COMPUTING AND GRAPHICS IN STATISTICS is based on the proceedings of the last two weeks of the six week IMA 1989 summer program "Robustness, Diagnostics, Computing and Graphics in Statistics". An important objective of the organizers was to draw a broad set of statisticians working in statistical computation into collaboration on the challenging problems in this rapidly developing area. We thank the organizers of the robustness and diagnostics program Werner Stuetzle, Luke Tierney, Edward Wegman, Allan R. Wilks, and especially Andreas Buja and Paul A. Tukey who edited the proceedings. We also take this opportunity to thank those agencies whose financial support made the summer program possible: the Air Force Office of Scientific Research, the Army Research Office, the National Science Foundation, the National Security Agency and the Office of Naval Research. A vner Friedman Willard Miller, Jr. PREFACE This volume covers the computational part of IMA activities in statistics during the summer of 1989. The areas of statistical computing and graphics encompass a broad range of research, much of it represented here. The vigor of this research is probably best demonstrated by the fact that as of this writing two new journals are being launched, both entirely dedicated to these areas.
Table of ContentsAn interface between S and Mathematica.- Looking at large data sets using binned data plots.- Integrating a robust option into a multiple regression computing environment.- Algorithm development for nonstandard least squares problems. Repeated categorical responses with missing values: A case study.- Importance sampling for Bayesian estimation.- A software model for statistical graphics.- Geometric abstractions for constrained optimization of layouts.- Construction of line densities for parallel coordinate plots.- GLIMPSE, a knowledge-based front end for GLIM.- GENSTAT as a computing environment.- Situations, summaries and model objects.- On estimation and visualization of higher dimensional surfaces.- Odds plots: A graphical aid for finding associations between views of a data set.- A Stochastic Approach to Load Balancing in Coarse Grain Parallel Computers.- Algorithms for choosing the domain and range when plotting a function.- High-dimensional depth-cuing for guided tours of multivariate data.- Towards a structured data analysis environment: A cognition-based design.