In the current paper the decoding algorithms for motor-related BCI systems for continuous upper limb trajectory prediction are considered. Two methods for the smooth prediction, namely Sobolev and Polynomial Penalized Multi-Way Partial Least Squares (PLS) regressions, are proposed. The methods are compared to the Multi-Way Partial Least Squares and Kalman Filter approaches. The comparison demon...

Partial Least Squares (PLS) is a standard statistical method in chemometrics. It can be considered as an incomplete, or “partial”, version of the Least Squares estimator of regression, applicable when high or perfect multicollinearity is present in the predictor variables. The Least Squares estimator is well-known to be an optimal estimator for regression, but only when the error terms are norm...

Partial least square (PLS) analysis is the most favourite tool in chemometrics to develop calibration models. PLS technique allows us decipher even complex systems by analysing all variables instead of looking at them one a time. not only capture maximum variation associated with predictor (i.e. spectra) and predicted concentration) but also maximises correlation between them. The present artic...

Title of dissertation: LOOKING AT PEOPLE USING PARTIAL LEAST SQUARES William Robson Schwartz Doctor of Philosophy, 2010 Dissertation directed by: Professor Larry S. Davis Analysis of images involving humans is of significant interest in computer vision because problems such as detection, modeling, recognition, and tracking are fundamental to model interactions between people and understand high...

An objective wavelength selection method is proposed for near-infrared (NIR) spectroscopy mainly to overcome the possible subjectivity introduced by moving window partial least squares regression (MWPLS). This improved procedure (iMWPLS) introduced an indicator to evaluate importance of each wavelength and then all wavelengths were ranked by these indicators. On the basis of the indicator ranki...

Citation: ter Braak, C. J. F. (1995). Non-linear methods for multivariate statistical calibration and their use in palaeoecology: a comparison of inverse (k-nearest neighbours, partial least squares and weighted averaging partial least squares) and classical approaches. Abstract Current environmental problems, such as acid rain and global warming, have greatly increased interest in fossil speci...

(1993). Weighted averaging partial least squares regression (WA-PLS): definition and comparison with other methods for species-environment calibration. ABSTRACT A multivariate calibration method is proposed that relates to correspondence analysis as partial least squares (PLS) relates to principal components analysis. The new method extends and improves the weighted averaging (WA) method for in...

Partial Least Squares (PLS) is a widely used technique in chemometrics, especially in the case where the number of independent variables is significantly larger than the number of data points. There are many articles on PLS [HTF01, GK86] but the mathematical details of PLS do not always come out clearly in these treatments. This paper is an attempt to describe PLS in precise and simple mathemat...

Partial least squares (PLS) is an efficient statistical regression technique that is highly suited for the analysis of genomic and proteomic data. In this article, we review both the theory underlying PLS as well as a host of bioinformatics applications of PLS. In particular, we provide a systematic comparison of the PLS approaches currently employed, and discuss analysis problems as diverse as...