Results 31 to 40 of about 86,229 (292)
Envelopes and Partial Least Squares Regression
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2013 SummaryWe build connections between envelopes, a recently proposed context for efficient estimation in multivariate statistics, and multivariate partial least squares (PLS) regression. In particular, we establish an envelope as the nucleus of both univariate and multivariate PLS, which opens the door to pursuing the same goals as PLS but using ...
Cook, R. D., Helland, I. S., Su, Z.
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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 +2 more
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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 +2 more
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Photonics, 2022 We aimed to identify the browning of white adipocytes using partial least squares regression (PLSR), infrared spectral biomarkers, and partial least squares discriminant analysis (PLS-DA) with FTIR spectroscopy instead of molecular biology.
Dong-Hyun Shon +4 more
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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
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The Degrees of Freedom of Partial Least Squares Regression [PDF]
Journal of the American Statistical Association, 2011 Preprint: Weierstraß-Institut für Angewandte Analysis und Stochastik, vol ...
Sugiyama, Masashi, Krämer, Nicole
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Scaled Predictor Envelopes and Partial Least-Squares Regression [PDF]
Technometrics, 2016 Partial least squares (PLS) is a widely used method for prediction in applied statistics, especially in chemometrics applications. However, PLS is not invariant or equivariant under scale transformations of the predictors, which tends to limit its scope to regressions in which the predictors are measured in the same or similar units. Cook et al. (2013)
R. Dennis Cook, Zhihua Su
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Fast Multiway Partial Least Squares Regression
IEEE Transactions on Biomedical Engineering, 2019 Multiway array decomposition has been successful in providing a better understanding of the structure underlying data and in discovering potentially hidden feature dependences serving high-performance decoder applications. However, the computational cost of multiway algorithms can become prohibitive, especially when considering large datasets ...
Camarrone, Flavio, Van Hulle, Marc M.
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On function-on-function regression: partial least squares approach [PDF]
Environmental and Ecological Statistics, 2020 Functional data analysis tools, such as function-on-function regression models, have received considerable attention in various scientific fields because of their observed high-dimensional and complex data structures. Several statistical procedures, including least squares, maximum likelihood, and maximum penalized likelihood, have been proposed to ...
Ufuk Beyaztas, Han Lin Shang
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, 2011 In recent years, Fourier Transform Infrared (FT-IR) spectroscopy has had an increasingly important role in the field of pathology and diagnosis of disease states.
Gunasekaran, S +2 more
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