Methodology and theory for partial least squares applied to functional data [PDF]
, 2012 The partial least squares procedure was originally developed to estimate the slope parameter in multivariate parametric models. More recently it has gained popularity in the functional data literature.
Aurore Delaigle, Peter Hall
openalex +4 more sources
semPLS: Structural Equation Modeling Using Partial Least Squares [PDF]
Journal of Statistical Software, 2012 Structural equation models (SEM) are very popular in many disciplines. The partial least squares (PLS) approach to SEM offers an alternative to covariance-based SEM, which is especially suited for situations when data is not normally distributed.
Armin Monecke, Friedrich Leish
doaj +4 more sources
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
Partial Least Squares Enhances Genomic Prediction of New Environments
Frontiers in Genetics, 2022 In plant breeding, the need to improve the prediction of future seasons or new locations and/or environments, also denoted as “leave one environment out,” is of paramount importance to increase the genetic gain in breeding programs and contribute to food
Osval A. Montesinos-López +8 more
doaj +1 more source
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
doaj +1 more source
Fault identification for chiller sensor based on partial least square method [PDF]
E3S Web of Conferences, 2021 Sensor failures can lead to an imbalance in heating, ventilation and air conditioning (HVAC) control systems and increase energy consumption. The partial least squares algorithm is a multivariate statistical method, compared with the principal component ...
Wu Bang +4 more
doaj +1 more source
Use of partial least squares regression to impute SNP genotypes in Italian Cattle breeds [PDF]
, 2013 Background The objective of the present study was to test the ability of the partial least squares regression technique to impute genotypes from low density single nucleotide polymorphisms (SNP) panels i.e. 3K or 7K to a high density panel with 50K SNP.
AJ Chamberlain +39 more
core +3 more sources
Penerapan Partial Least Squares Pada Data Gingerol
ComTech, 2010 Multivariate calibration model aims to predict the expensive measures obtained by using the measures of a cheap and easy. There are several problems that often occur in the model calibration, among others, and multikolinear. To overcome these problems we
Margaretha Ohyver
doaj +1 more source