Ž . Ž PLS-regression PLSR is the PLS approach in its simplest, and in chemistry and technology, most used form two-block . predictive PLS . PLSR is a method for relating two data matrices, X and Y, by a linear multivariate model, but goes beyond traditional regression in that it models also the structure of X and Y. PLSR derives its usefulness from its ability to analyze data with many, noisy, ...

This study aims to investigate the impact of service quality dimensions (tangibility, reliability, responsiveness, assurance, empathy) on market share Jordanian hotels. The sample this comprised general managers A total 162 respondents were surveyed via a self-administered survey. Partial least squares structural equation modeling using Smart PLS 3.3.9 software was used analyze data. findings i...

Histone deacetylase 2 is a promising target for drug intervention and its inhibitors are useful in treating cancer. QSAR (2D and 3D) studies were performed on a series of N-(2-Aminophenyl)-Benzamide derivatives using Cerius2 software (accelrys). QSAR study performed on 25 analogues of which 21 were used in the training set and the rest 4 considered for the test set. 2DQSAR study performed using...

The pls package implements principal component regression (PCR) and partial least squares regression (PLSR) in R (R Development Core Team 2006b), and is freely available from the Comprehensive R Archive Network (CRAN), licensed under the GNU General Public License (GPL). The user interface is modelled after the traditional formula interface, as exemplified by lm. This was done so that people us...

The main contributions of this paper can be summarized as follows. First, we compare the Partial Least Squares (PLS) and the Principal Component Analysis (PCA), under fairly general conditions. (In particular, the existence of a true linear regression is not assumed.) We prove that PLS and PCA are equivalent, to within a rst-order approximation, hence providing a theoretical explanation for emp...

The partial least squares (PLS) regression is a new multivariate data analysis method. In this paper, based on the ideas of PLS model and feature fusion, a new non-iterative PLS algorithm and a novel method of feature fusion are proposed. The proposed method comprises three steps: firstly, extracting two sets of feature vectors with the same pattern and establishing PLS criterion function betwe...