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Svante Wold
Researcher at Umeå University
Publications - 330
Citations - 47686
Svante Wold is an academic researcher from Umeå University. The author has contributed to research in topics: Partial least squares regression & Principal component analysis. The author has an hindex of 70, co-authored 330 publications receiving 43606 citations.
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Principal component analysis
TL;DR: Principal Component Analysis is a multivariate exploratory analysis method useful to separate systematic variation from noise and to define a space of reduced dimensions that preserve noise.
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PLS-regression: a basic tool of chemometrics
TL;DR: PLS-regression (PLSR) as mentioned in this paper is the PLS approach in its simplest, and in chemistry and technology, most used form (two-block predictive PLS) is a method for relating two data matrices, X and Y, by a linear multivariate model.
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Cross-Validatory Estimation of the Number of Components in Factor and Principal Components Models
TL;DR: In this article, the rank estimation of the rank A of the matrix Y, i.e., the estimation of how much of the data y ik is signal and how much is noise, is considered.
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The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses
TL;DR: In this article, the use of Partial Least Squares (PLS) for handling collinearities among the independent variables X in multiple regression is discussed, and successive estimates are obtained using the residuals from previous rank as a new dependent variable y.
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Orthogonal projections to latent structures (O-PLS)
Johan Trygg,Svante Wold +1 more
TL;DR: In this article, a generic preprocessing method for multivariate data, called orthogonal projections to latent structures (O-PLS), is described, which removes variation from X (descriptor variables) that is not correlated to Y (property variables, e.g. yield, cost or toxicity).