Capturing functional connectomics using Riemannian partial least squares [PDF]
Scientific Reports, 2023 For neurological disorders and diseases, functional and anatomical connectomes of the human brain can be used to better inform targeted interventions and treatment strategies.
Matthew Ryan +3 more
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A non-linear partial least squares based on monotonic inner relation [PDF]
Frontiers in PhysiologyA novel regression model, monotonic inner relation-based non-linear partial least squares (MIR-PLS), is proposed to address complex issues like limited observations, multicollinearity, and nonlinearity in Chinese Medicine (CM) dose-effect relationship ...
Xuepeng Zheng +8 more
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Comparison between the Conventional Partial Least Squares (Pls) and the Robust Partial Least Squares (Rpls-Sem) Through Winsorization Approach [PDF]
Journal of Information Technology Management, 2022 This study compared the performance of the partial least squares-structural equation modelling (PLS-SEM) and the robust partial least squares -structural equation modelling (RPLS-SEM) methods through Winsorisation approach The inputs and the outputs used
GholamReza Zandi +3 more
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New Developments in Sparse PLS Regression
Frontiers in Applied Mathematics and Statistics, 2021 Methods based on partial least squares (PLS) regression, which has recently gained much attention in the analysis of high-dimensional genomic datasets, have been developed since the early 2000s for performing variable selection.
Jérémy Magnanensi +6 more
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Penalized partial least squares for pleiotropy
BMC Bioinformatics, 2021 Background The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects.
Camilo Broc +2 more
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Novel Kernel Orthogonal Partial Least Squares for Dominant Sensor Data Extraction
IEEE Access, 2020 Orthogonal Partial Least Squares (OPLS) methods are aimed at finding the dominant factors from predictor variables that can maximize cross-covariance between the factors themselves and response variables while a high correlation between them should also ...
Bo-Wei Chen
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Recursive N-way partial least squares for brain-computer interface. [PDF]
PLoS ONE, 2013 In the article tensor-input/tensor-output blockwise Recursive N-way Partial Least Squares (RNPLS) regression is considered. It combines the multi-way tensors decomposition with a consecutive calculation scheme and allows blockwise treatment of tensor ...
Andrey Eliseyev, Tetiana Aksenova
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Interval partial least squares and moving window partial least squares in determining the enantiomeric composition of tryptophan by using UV-Vis spectroscopy [PDF]
Journal of the Serbian Chemical Society, 2016 The application of interval partial least squares (IPLS) and moving window partial least squares (MWPLS) to the enantiomeric analysis of tryptophan (Trp) was investigated. A UV-Vis spectroscopy method for determining the enantiomeric composition
Jiao Long +3 more
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Compressor map regression modelling based on partial least squares [PDF]
Royal Society Open Science, 2018 In this work, two kinds of partial least squares modelling methods are applied to predict a compressor map: one uses a power function polynomial as the basis function (PLSO), and the other uses a trigonometric function polynomial (PLSN).
Xu Li +6 more
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Marginal Screening for Partial Least Squares Regression
IEEE Access, 2017 Partial least squares (PLS) regression is a versatile modeling approach for high-dimensional data analysis. Recently, PLS-based variable selection has attracted great attention due to high-throughput data reduction and modeling interpretability.
Naifei Zhao, Qingsong Xu, Hong Wang
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