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. 2015 Nov 2;5:15925. doi: 10.1038/srep15925

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Copyright © 2015, Macmillan Publishers Limited

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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The model consists of two predictive component (p1,p2) shown in the figure and three orthogonal components (not shown). t[1] = scores for predictive component 1, t [2] = scores for predictive component 2. The model explains 41.9% of the variation in x-space and 51.1% of the variation in y-space. Explained variation of each components: R²X_p1 = 0.145; R²X_p2 = 0.02; R²X_o = 0.274. Goodness of prediction Q²_cum = 0.461. CWP (), NP () and CON (). The ellipse shows the 95% confidence interval using Hotelling T² statistics.

Inline graphic — The model consists of two predictive component (p1,p2) shown in the figure and three orthogonal components (not shown). t[1] = scores for predictive component 1, t [2] = scores for predictive component 2. The model explains 41.9% of the variation in x-space and 51.1% of the variation in y-space. Explained variation of each components: R²X_p1 = 0.145; R²X_p2 = 0.02; R²X_o = 0.274. Goodness of prediction Q²_cum = 0.461. CWP (), NP () and CON (). The ellipse shows the 95% confidence interval using Hotelling T² statistics.