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Eigenvector Research Inc eigenvector research pls toolbox version 9.2.1
Eigenvector Research Pls Toolbox Version 9.2.1, supplied by Eigenvector Research Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/pls_toolbox+version+9%2E2%2E1/eigenvector+pls+toolbox/pmc11966258-69-9-15
Average 90 stars, based on 1 article reviews
eigenvector research pls toolbox version 9.2.1 - by Bioz Stars, 2026-09
90/100 stars

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Article Title: Chemometrically driven multiplexed metal ion detection using a triple emitting quantum dots–based nanoprobe
Article Snippet: In the case of binary and ternary metal ion mixtures, the accuracy of PLS and U-PLS models was evaluated based on RMSECV, RMSEP, R 2 CV , and R 2 P . The PCA, PLS, and PLS-DA models and respective calculations were performed in Matlab 2023a environment (MathWorks, Natick, MA, USA), using the PLS Toolbox version 9.2.1 (Eigenvector Research Inc., Wenatchee, WA, USA).

Article Title: Chemometrically driven multiplexed metal ion detection using a triple emitting quantum dots-based nanoprobe.
Article Snippet: RMSE = � ∑N i=1 � ŷi − yi �2 N The PCA, PLS, and PLS-DA models and respective calculations were performed in Matlab 2023a environment (MathWorks, Natick, MA, USA), using the PLS Toolbox version 9.2.1 (Eigenvector Research Inc., Wenatchee, WA, USA).

Article Title: Application of NIR Spectroscopy for the Valorisation of Cork By-Products: A Feasibility Study over the Screening and Discrimination of Chemical Compounds of Interest
Article Snippet: All the calculations and models were made in the Matlab 2023a environment version 9.14.0.2254940 (MathWorks, Natick, MA, USA), also using the PLS Toolbox version 9.2.1 (Eigenvector Research Inc., Wenatchee, WA, USA).

Article Title: Discrimination and Quantification of Cotton and Polyester Textile Samples Using Near-Infrared and Mid-Infrared Spectroscopies
Article Snippet: RPD values < 1.0 indicate very poor model predictions and their use is not recommended; RPD between 1.0 and 1.4 indicate poor model predictions; RPD between 1.4 and 1.8 indicate fair predictions; between 1.8 and 2.0 indicate good predictions; between 2.0 and 2.5 indicate very good predictions; and RPD > 2.5 indicate excellent model predictions [ ]. (3) R P D = s t d R M S E P Matlab version R2023a (MathWorks, Natick, MA, USA) and the PLS Toolbox version 9.2.1 (Eigenvector Research Incorporated, Manson, WA, USA) were used for all the calculations.



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