Grand Tour and Projection Pursuit

1 September 1995

journal article
research article
Published by Taylor & Francis in Journal of Computational and Graphical Statistics

Vol. 4 (3) , 155-172
https://doi.org/10.1080/10618600.1995.10474674

Abstract

The grand tour and projection pursuit are two methods for exploring multivariate data. We show how to combine them into a dynamic graphical tool for exploratory data analysis, called a projection pursuit guided tour. This tool assists in clustering data when clusters are oddly shaped and in finding general low-dimensional structure in high-dimensional, and in particular, sparse data. An example shows that the method, which is projection-based, can be quite powerful in situations that may cause grief for methods based on kernel smoothing. The projection pursuit guided tour is also useful for comparing and developing projection pursuit indexes and illustrating some types of asymptotic results.

Keywords

This publication has 14 references indexed in Scilit:

Prosection Views: Dimensional Inference through Sections and Projections
Journal of Computational and Graphical Statistics, 1994
Analyzing High-Dimensional Data with Motion Graphics
SIAM Journal on Scientific and Statistical Computing, 1990
On Polynomial-Based Projection Indices for Exploratory Projection Pursuit
The Annals of Statistics, 1989
Exploratory Projection Pursuit
Journal of the American Statistical Association, 1987
What is Projection Pursuit?
Journal of the Royal Statistical Society Series A: Statistics in Society, 1987
Projection Pursuit
The Annals of Statistics, 1985
The Grand Tour: A Tool for Viewing Multidimensional Data
SIAM Journal on Scientific and Statistical Computing, 1985
Asymptotics of Graphical Projection Pursuit
The Annals of Statistics, 1984
Transformations of Multivariate Data
Published by JSTOR ,1971
Van Hove Analysis of the Reactions $π^{-} p \to π^{-} π^{-} π^{+} p$ and $π^{+} p \to π^{+} π^{+} π^{-} p$ at 16 GeV/c
Physical Review D, 1971