Influence analysis of non-Gaussianity by applying projection pursuit

Yufen Huang, Ching-Ren Cheng and Tai-Ho Wang

Statistics & Probability Letters, 2007, vol. 77, issue 14, 1515-1521

Abstract: The Gaussian distribution is the least structured from the information-theoretic point of view. In this paper, projection pursuit is used to find non-Gaussian projections to explore the clustering structure of the data. We use kurtosis as a measure of non-Gaussianity to find the projection directions. Kurtosis is well known to be sensitive to influential points/outliers, and so the projection direction will be greatly affected by unusual points. We also develop the influence functions of projection directions to investigate abnormal observations. A data example illustrates the application of these approaches.

Keywords: Influence; function; Kurtosis; Non-Gaussianity; Projection; pursuit (search for similar items in EconPapers)
Date: 2007
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