An Instrument Surveillance and Calibration Verification (ISCV) system primarily consists of a process model, which is used to verify the output of the measurement instruments in that process. Artificial Neural Networks (ANNs) and Partial Least Squares (PLS) are two methods, which can be used for model development. The linear transformation of the PLS method provides a supervised reduction of th...

High order partial least squares (HOPLS) is a novel data processing method. It is highly suitable for building prediction model which has tensor input and output. The objective of this study is to build a prediction model of the relationship between sinoatrial node field potential and high glucose using HOPLS. The three sub-signals of the sinoatrial node field potential made up the model's inpu...

Early detection of cancer is crucial for successful treatments. In this paper, we propose a multiclass Logistic Partial Least Squares (LPLS) algorithm for classification of normal vs. cancer using Mass Spectrometry (MS). LPLS combines the multiclass logistic regression with Partial Least Squares (PLS) algorithm. Wavelet decomposition is also proposed for pre-processing of original data. Wavelet...

ATR-FTIR (Attenuated Total Reflectance Fourier Transform Infrared) spectra of prehardened epoxies with varying amounts of hardener and resin (mix ratio) have been acquired on a Midac FTIR spectrometer. The spectra form a set of training spectra for partial least-squares (PLS) analysis which was then used to analyze a series of epoxies of unknown mix ratio. The PLS model predicted the unknown mi...

We present an extension of PLS—called partial least squares correspondence analysis (PLSCA)—tailored for the analysis of nominal data. As the name indicates, PLSCA combines features of PLS (analyzing the information common to two tables) and correspondence analysis (CA, analyzing nominal data). We also present inferential techniques for PLSCA such as bootstrap, permutation, and χ2 omnibus tests...

A quantitative structure-antioxidant activity relationship (QSAR) study of 36 flavonoids was performed using the partial least squares projection of latent structures (PLS) method. The chemical structures of the flavonoids have been characterized by constitutional descriptors, two-dimensional topological and connectivity indices. Our PLS model gave a proper description and a suitable prediction...

Voluminous studies use Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze data. One of the reasons for using PLS-SEM is when structural model complex. Studies employing complex models with many constructs and indicators lead selection analysis. The purposes assessing measurement are examine basic dimensions construct variables, validate dimensions, determine number each con...

Composite-based methods like partial least squares (PLS) path modeling have an advantage over factor-based methods (like CB-SEM) because they yield determinate predictions, while factor-based methods’ prediction is constrained in this regard by factor indeterminacy. To maximize practical relevance, research findings should extend beyond the study’s own data. We explain how PLS practices, derivi...