Optimised score plot by principal components of predictions Export

@article{citeulike:3187425, abstract = {A common problem in statistics/chemometrics is to relate two data matrices (X and Y) to each other, with the purpose of either prediction or interpretation. Usually, one is interested in understanding which directions in Y-space that can be predicted by which directions in X-space. Several methods exist for this, for instance, PLS regression and canonical correlation. The present paper presents a new plot for visualising the relationship between X and Y. The plot is based on a decomposition of the X-space that is optimal with respect to Y-variance. The new procedure can accompany any regression method.}, author = {Langsrud, O.}, booktitle = {Selected papers presented at the 2nd International Symposium on PLS and Related Methods held in Anacapri (Naples), Italy October 1-3, 2001}, citeulike-article-id = {3187425}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/S0169-7439(03)00088-1}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S0169-7439(03)00088-1}, citeulike-linkout-2 = {http://www.sciencedirect.com/science/article/B6TFP-48WB6SY-1/2/275e246ed0f0480192274a78cb7e89e2}, day = {28}, doi = {10.1016/S0169-7439(03)00088-1}, issn = {01697439}, journal = {Chemometrics and Intelligent Laboratory Systems}, keywords = {modeling, statistics}, month = {October}, number = {1-2}, pages = {61--74}, posted-at = {2008-09-03 19:23:40}, priority = {2}, title = {Optimised score plot by principal components of predictions}, url = {http://dx.doi.org/10.1016/S0169-7439(03)00088-1}, volume = {68}, year = {2003} }

TY - JOUR ID - citeulike:3187425 L3 - citeulike-article-id:3187425 N2 - A common problem in statistics/chemometrics is to relate two data matrices (X and Y) to each other, with the purpose of either prediction or interpretation. Usually, one is interested in understanding which directions in Y-space that can be predicted by which directions in X-space. Several methods exist for this, for instance, PLS regression and canonical correlation. The present paper presents a new plot for visualising the relationship between X and Y. The plot is based on a decomposition of the X-space that is optimal with respect to Y-variance. The new procedure can accompany any regression method. IS - 1-2 JF - Chemometrics and Intelligent Laboratory Systems SN - 01697439 EP - 74 TI - Optimised score plot by principal components of predictions VL - 68 T2 - Selected papers presented at the 2nd International Symposium on PLS and Related Methods held in Anacapri (Naples), Italy October 1-3, 2001 SP - 61 KW - modeling KW - statistics AU - Langsrud, O PY - 2003/10/28/ UR - http://dx.doi.org/10.1016/S0169-7439(03)00088-1 ER -