Selecting and Ordering Components in Functional-Data Linear Prediction
For some fifty years the problem of basis choice, in linear prediction problems based on high-dimensional data, has been under discussion. From some viewpoints the debate is no closer to resolution today than in the past. We shall discuss the issues involved, describe theoretical results which shed light on the debate, and introduce methodology that is appropriate in cases where non-standard techniques can be effective.
KeywordsDimension Reduction Linear Prediction Order Component Basis Choice Orthonormal Eigenvector
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