Abstract
Projection pursuit is a computer-intensive method for statistical analysis which intends to clarify property of multivariate data by projecting them onto a lower-dimensional subspace. In practice, the projection pursuit is performed based on an algorithm to find a lower-dimensional subspace by maximizing an objective function called projection index which is a measure of interestingness of the projected data. In this paper, we try to evaluate how the direction of projection determined in the process of the projection pursuit is affected by perturbation of the data points.
