Type of Tool | R-Function |
Title | Multivariate Partial Least Squares (R) |
Programmer/Email | Danh Nguyen |
Contributing Site | Davis |
Description | This function computes the K PLS components based on X & Y matrices and associated quantities. Y can be a vector or a matrix of multiple responses. |
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References | SAS Institute Inc. (1999). The PLS procedure. SAS/STAT User's Guide, Version 8, Cary, NC, pp. 2693-2734. Wold, S. (1994). PLS for multivariate linear modeling. In Waterbeemed, H. (ed), Chemometric Methods in Molecular Design, Verlag-Chemie, Germany, pp. 195-218. |
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Software Program | R |
Software | R |
Macro Parameters | Input argument(s) X_s Matrix of predictors (genes)--standardized to mean 0 variance 1 variance 1 ("training X" of size n x p). Y_s Matrix (or vector) of responses Y_s--also standardized ("training Y" of size nxL). X_ps Matrix of predictor values (test/validation X) to construct test components, X_ps (of size mxp). lv The number of PLS components (lv). Return(s): T1 n x lv matrix of PLS training components based on training information. T2 m x lv matrix of PLS test components contructed from training information. PVEX 1 x lv vector of cummulative percent of X-variation explained. PVEY 1 x lv vector of cummulative percent of Y-variation explained. W p x lv matrix of X-weights. B p x 1 vector of "regression coefficients". V p x 1 vector of linear combination of sum of squares of X-weights This is the so called 'VIP' (variable influence on projection) (Wold 1994; SAS Institue Inc., 1999). |
R-Code - Attachment | Davis_Partial Least Squares_R Function |
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Special Features Text | * X is standardized so rank(X)=n-1 so maximum value that lv can take is n-1. * Also, to get the correct test components the standardization of the test data X_p (denoted X_ps) needs to be done properly; i.e. based on column means and variance from the training data. X_ps is obtained by call to function STANDARDIZE_PRED.m. |
Notes1-Legend | Section with calls to needed macros |
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Notes2-Legend | Macro call with fully specified parameters |
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Notes3-Legend | Section with definitions of global macro parameters |
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Notes4-Legend | Section with definitions of local macro variables |
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See Also | Partial Least Squares Research Topic Partial Least Squares SAS |
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Stat Tools Disclaimer | History: Date/Last Modified: 10.28.01/07.19.01 (Danh V. Nguyen), Matlab code. Translated to R in 2007 (Ying Chen). Full testing of exact correspondence of results to Matlab, R and SAS 08.14.08 (D.V. Nguyen). |
Discliamer | The views expressed within CTSpedia are those of the author and must not be taken to represent policy or guidance on the behalf of any organization or institution with which the author is affiliated. |
Permission | Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF ERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT OLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
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