2011年11月1日 · In this work, a Partial Least Squares (PLS) regression model using Near-Infrared (NIR) spectroscopy was developed to monitor the progress of the catalyzed transesterification reactions of soybean oil that produce biodiesel. The NIR spectra were collected during the transesterification reaction with a lab made spectrophotometric flow cell.

regularized partial least squares (RPLS) is introduced in Section 2. In Section 3, we introduce two novel extensions of PLS and RPLS: non-negative PLS and generalized PLS (GPLS) for structured data. We illustrate the comparative strengths of our approach in Sections 4 and 5 through simulation studies and a case study on NMR spectroscopy

2012年4月17日 · We also outline extensions of our methods leading to novel methods for Non-negative PLS and Generalized PLS, an adaption of PLS for structured data. We demonstrate the utility of our methods through simulations and a case study on proton Nuclear Magnetic Resonance (NMR) spectroscopy data.

2017年4月24日 · To investigate the quantitative performance of 400 MHz 1 H NMR spectra for measuring ethanol, a full-spectrum five-component mean-centered PLS model between the spectral data and the ethanol concentration of the juice samples was calculated.

2012年4月18日 · In this paper, we report multivariate analyses, such as principal component analysis and partial least-squares regression, of NMR spectra of poly(N-isopropylacrylamide)s [poly(NIPAAm)s].

2011年2月7日 · In the present study, we propose an alternative to PLS-DA in which we combine NMR and DART-MS data to discover potential serum biomarkers for breast cancer. Instead of using a dummy Y matrix, we select a more meaningful Y vector in the PLS regression, using the first principal component from the PCA of the NMR data.

2013年8月1日 · We introduce a framework for Regularized PLS by solving a relaxation of the SIMPLS optimization problem with penalties on the PLS loadings vectors. Our approach enjoys many advantages including flexibility, general penalties, easy interpretation of results, and fast computation in high-dimensional settings.

Collection of modelling algorithms for NMR & MS data, including principal components analysis (PLS), (orthogonal) partial least squares (O-PLS, PLS), non-negative least squares regression (NNLSQ). Included are model visualisations based on matplotlib.

2013年8月1日 · We also outline extensions of our methods leading to novel methods for non-negative PLS and generalized PLS, an adoption of PLS for structured data. We demonstrate the utility of our methods through simulations and a case study on proton Nuclear Magnetic Resonance (NMR) spectroscopy data.

2018年3月5日 · Partial least squares (PLS) analysis was applied directly to a variety of simulated time-domain relaxation data under diverse conditions to predict constituent content and results were compared to the standard analysis methods. For many situations, PLS analysis displayed superior performance for quantification than the standard analyses.