Results 21 to 30 of about 614,693 (221)

On Fuzzy Regression Adapting Partial Least Squares [PDF]

, 2011
Partial Least Squared (PLS) regression is a model linking a dependent variable y to a set of X (numerical or categorical) explanatory variables. It can be obtained as a series of simple and multiple regressions of simple and multiple regressions. PLS is an alternative to classical regression model when there are many variables or the variables are ...
A. BASARAN, SIMONETTI, BIAGIO, D'AMBRA, LUIGI   +2 more
openaire   +3 more sources

A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regression.

Journal of Experimental Botany, 2021
Partial least squares regression (PLSR) modelling is a statistical technique for correlating datasets, and involves the fitting of a linear regression between two matrices.
A. C. Burnett, Jeremiah Anderson, Kenneth J Davidson, Kim S. Ely, J. Lamour, Qianyu Li, B. Morrison, Dedi Yang, A. Rogers, S. Serbin   +9 more
semanticscholar   +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, Chuanlei Yang, Yinyan Wang, Hechun Wang, Xianghuan Zu, Yongrui Sun, Song Hu   +6 more
doaj   +1 more source

Evaluation of groundwater quality for agricultural under different conditions using water quality indices, partial least squares regression models, and GIS approaches

Applied Water Science, 2022
Evaluating grouLindwater quality and associated hydrochemical properties is critical to manage groundwater resources in arid and semiarid environments.
M. Masoud, M. El Osta, Abdulaziz Alqarawy, S. Elsayed, M. Gad   +4 more
semanticscholar   +1 more source

Partial Least Squares Regression for Binary Responses and Its Associated Biplot Representation

Mathematics, 2022
In this paper, we propose a generalization of Partial Least Squares Regression (PLS-R) for a matrix of several binary responses and a a set of numerical predictors. We call the method Partial Least Squares Binary Logistic Regression (PLS-BLR).
Laura Vicente-Gonzalez , Jose Luis Vicente-Villardon   +1 more
doaj   +1 more source

Group‐wise partial least square regression

Journal of Chemometrics, 2017
AbstractThis paper introduces the group‐wise partial least squares (GPLS) regression. GPLS is a new sparse PLS technique where the sparsity structure is defined in terms of groups of correlated variables, similarly to what is done in the related group‐wise principal component analysis. These groups are found in correlation maps derived from the data to
José Camacho, Edoardo Saccenti
openaire   +5 more sources

Partial least squares regression in the social sciences [PDF]

Tutorials in Quantitative Methods for Psychology, 2015
Partial least square regression (PLSR) is a statistical modeling technique that extracts latent factors to explain both predictor and response variation.
Megan L. Sawatsky, Matthew Clyde, Fiona Meek   +2 more
doaj   +2 more sources

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, APW de Roos, BJ Hayes, BJ Hayes, BJ Hayes, BL Browning, C Dimauro, C Hagger, Corrado Dimauro, D Boichard, D Segelke, DP Berry, G Li, G Moser, Gabriele Marras, GCB Schopen, Giustino Gaspa, H Abdi, HA Mulder, HD Daetwyler, I Medugorac, J Chen, JE Pryce, JM Hickey, K Kizilkaya, KA Weigel, KA Weigel, Massimo Cellesi, Nicolò PP Macciotta, P Ajmone-Marsan, P Scheet, Paolo Ajmone-Marsan, PM VanRaden, R Dassonneville, R Dassonneville, Roberto Steri, T Druet, T Druet, TH Meuwissen, Z Zhang   +39 more
core   +3 more sources

PARTIAL LEAST SQUARES REGRESSION $PLS$ ON INTERVAL DATA

Revista de la Facultad de Ciencias, 2016
Uncertainty in the data can be considered as a numerical interval in which a variable can assume its possible values, this has been known as interval data. In this paper the $PLS$ regression methodology is extended to the case where explanatory, response
Carlos Alberto Gaviria-Peña, Raúl Alberto Pérez-Agamez, María Eugenia Puerta-Yepes   +2 more
doaj   +1 more source

APPLICATION OF PARTIAL LEAST SQUARES REGRESSION FOR AUDIO-VISUAL SPEECH PROCESSING AND MODELING [PDF]

Научно-технический вестник информационных технологий, механики и оптики, 2015
Subject of Research. The paper deals with the problem of lip region image reconstruction from speech signal by means of Partial Least Squares regression. Such problems arise in connection with development of audio-visual speech processing methods.
A. L. Oleinik
doaj   +1 more source