Article ID Journal Published Year Pages File Type
416730 Computational Statistics & Data Analysis 2006 23 Pages PDF
Abstract

Partial least squares (PLS) is a modeling technique that has met with considerable success, particularly in the fields of chemometrics and psychometrics. In this paper, we extend linear PLS to a nonlinear version called “reciprocal curves.” Reciprocal curves are smooth one-dimensional curves that pass through the center of the data, are co-consistent and share several optimality properties originally identified with PLS.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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