Projection Pursuit

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Functional Projection Pursuit

This article describes the adaption of exploratory projection pursuit for use with functional data. The aim is to nd \interesting" projections of functional data: e.g. to separate curves into meaningful clusters. Functional data are projected onto low-dimensional subspaces determined by a projection function using a suitable inner product. Such a projection is rapidly computed by representing d...

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Oblique Projection Matching Pursuit

Recent theory of compressed sensing (CS) tells us that sparse signals can be reconstructed from a small number of random samples. In reconstruction of sparse signals, greedy algorithms, such as the orthogonal matching pursuit (OMP), have been shown to be computationally efficient. In this paper, the performance of OMP is shown to be dependent on how well information of the underlying signals is...

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Localized Exploratory Projection Pursuit

Based on CART, we introduce a recursive partitioning method for high dimensional space which partitions the data using low dimensional features. The low dimensional features are extracted via an exploratory projection pursuit (EPP) method, localized to each node in the tree. In addition, we present an exploratory splitting rule that is potentially less biased to the training data. This leads to...

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Three-Dimensional Projection Pursuit

The development and usage of a three-dimensional projection pursuit software package is discussed. The well-established Jones and Sibson moments index is chosen as a computationally efficient projection index to extend to 3D. Computer algebraic methods are extensively employed to handle the long and complex formulae that constitute the index and are explained in detail. A discussion of importan...

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Projection Pursuit Regression

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ژورنال

عنوان ژورنال: The Annals of Statistics

سال: 1985

ISSN: 0090-5364

DOI: 10.1214/aos/1176349519