Partial least squares (PLS) was not originally designed as a tool for statistical discrimination. In spite of this, applied scientists routinely use PLS for classification and there is substantial empirical evidence to suggest that it performs well in that role. The interesting question is: why can a procedure that is principally designed for overdetermined regression problems locate and emphas...

Methods of multiblock bilinear factorizations have increased in popularity in chemistry and biology as recent increases in the availability of information-rich spectroscopic platforms has made collecting multiple spectroscopic observations per sample a practicable possibility. Of the existing multiblock methods, consensus PCA (CPCA-W) and multiblock PLS (MB-PLS) have been shown to bear desirabl...

Typically, flow volumes are visualized by defining their boundary as iso-surface of a level set function. Grid-based level sets offer a good global representation but suffer from numerical diffusion of surface detail, whereas particlebased methods preserve details more accurately but introduce the problem of unequal global representation. The particle level set (PLS) method combines the advanta...

Use of the partial least squares (PLS) method has been on the rise among e-collaboration researchers. It has also seen increasing use in a wide variety of fields of research. This includes most business-related disciplines, as well as the social and health sciences. The use of the PLS method has been primarily in the context of PLS-based structural equation modeling (SEM). This article discusse...

We compare a number of data-rich prediction methods that are widely used in macroeconomic forecasting with a lesser known alternative: partial least squares (PLS) regression. In this method, linear, orthogonal combinations of a large number of predictor variables are constructed such that the covariance between a target variable and these common components is maximized. We show theoretically th...

Partial least squares (PLS) is one of the most common regression algorithms in chemistry, relating input–output samples (x i , y i) by a linear multivariate model. In this paper we analyze the PLS algorithm under a specific probabilistic model for the relation between x and y. Following Beer's law, we assume a linear mixture model in which each data sample (x, y) is a random realization from a ...

BACKGROUND Papillon-Lefevre Syndrome (PLS) is a rare autosomal recessive disorder characterized by diffused palmoplantar keratoderma and severe periodontitis. Increased susceptibility to infections due to impairment of the immune system is considered to be involved in pathoetiology of this disease. OBJECTIVES According to the crucial function of HLA molecules in immune responses and associati...

As the performance of BIM could be impaired when unidentified risks are present during implementation, it has become important for construction industry different countries to identify these risk factors as well causal relationships amongst them. In Nigeria, while impacting implementation have been identified, no attempt exist unravel relationship factors. This study thus, aims assess in Nigeri...

Phospholipids (PLs) are the important components of cell membrane of all living organisms. The PL or the cell membrane of the bacteria are the least studied subject as it involves large quantities of material and few methods to assay. The novel study was designed to understand if the cell membrane remains same or it changes during different conditions. The bacteria, Acidithiobacillus ferrooxida...

We investigate Newton-type optimization methods for solving piecewise linear systems (PLS) with non-degenerate coefficient matrix. Such systems arise, for example, from the numerical solution of linear complementarity problem which is useful to model several learning and optimization problems. In this paper, we propose an effective damped Newton method, namely PLSDN, to find the exact solution ...