Plsrsgn: Difference between revisions
Jump to navigation
Jump to search
imported>Jeremy (Importing text file) |
imported>Jeremy (Importing text file) |
||
| Line 1: | Line 1: | ||
===Purpose=== | ===Purpose=== | ||
Generates a matrix used to calculate residuals from a single data block using partial least squares regression models. | Generates a matrix used to calculate residuals from a single data block using partial least squares regression models. | ||
===Synopsis=== | ===Synopsis=== | ||
:coeff = plsrsgn(data,lv,out) | :coeff = plsrsgn(data,lv,out) | ||
===Description=== | ===Description=== | ||
coeff = plsrsgn(data,lv) calculates a matrix coeff from a single data block data. plsrsgn calculates partial least squares regression models of each variable in the matrix data using the remaining variables and the number of latent variables lv. Multiplying a new data matrix by the matrix coeff yields a matrix whose values are the difference between the new data and it's prediction based on the PLS regressions created by plsrsgn. | coeff = plsrsgn(data,lv) calculates a matrix coeff from a single data block data. plsrsgn calculates partial least squares regression models of each variable in the matrix data using the remaining variables and the number of latent variables lv. Multiplying a new data matrix by the matrix coeff yields a matrix whose values are the difference between the new data and it's prediction based on the PLS regressions created by plsrsgn. | ||
===See Also=== | ===See Also=== | ||
[[plsrsgcv]], [[replace]] | [[plsrsgcv]], [[replace]] | ||
Revision as of 15:26, 3 September 2008
Purpose
Generates a matrix used to calculate residuals from a single data block using partial least squares regression models.
Synopsis
- coeff = plsrsgn(data,lv,out)
Description
coeff = plsrsgn(data,lv) calculates a matrix coeff from a single data block data. plsrsgn calculates partial least squares regression models of each variable in the matrix data using the remaining variables and the number of latent variables lv. Multiplying a new data matrix by the matrix coeff yields a matrix whose values are the difference between the new data and it's prediction based on the PLS regressions created by plsrsgn.