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Tests in projection pursuit regression

✍ Scribed by Meekyong G. Park; Jiayang Sun

Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
195 KB
Volume
75
Category
Article
ISSN
0378-3758

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✦ Synopsis

Projection Pursuit regression (PPR) approximates a regression function f(X ) by a ÿnite sum of ridge functions L l=1 f l ( T l X ). When the explanatory vector X is normally distributed, Johansen and Johnstone (1990) gave an one-term approximation formula to the signiÿcance level of a test of H0: f=constant. In this paper, we generalize the one-term approximation to a two-term approximation and to the case when X has an arbitrary distribution based on a general projection pursuit regression index that we propose. The ÿrst term of our approximation is same as Johansen and Johnstone's one-term approximation when X is normally distributed. Some simulations and applications will be presented and choices of L will be discussed.

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