Simpls: Difference between revisions
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===Purpose=== | ===Purpose=== | ||
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* '''x''' = X-block (predictor block) class "double" or "dataset", and | * '''x''' = X-block (predictor block) class "double" or "dataset", and | ||
* '''y''' = Y-block (predicted block) class "double" or "dataset". | * '''y''' = Y-block (predicted block) class "double" or "dataset". | ||
====Optional Inputs==== | |||
* '''''ncomp''''' = integer, number of latent variables to use in {default = rank of X-block}, and | * '''''ncomp''''' = integer, number of latent variables to use in {default = rank of X-block}, and | ||
* '''options''' = a structure array discussed below. | |||
====Outputs==== | |||
* '''reg''' = matrix of regression vectors, | * '''reg''' = matrix of regression vectors, | ||
* '''ssq''' = the sum of squares captured (ssq), | * '''ssq''' = the sum of squares captured (ssq), | ||
* '''xlds''' = X-block loadings, | * '''xlds''' = X-block loadings, | ||
* '''ylds''' = Y-block loadings, | * '''ylds''' = Y-block loadings, | ||
* '''wts''' = X-block weights, | * '''wts''' = X-block weights, | ||
* '''xscrs''' = X-block scores, | * '''xscrs''' = X-block scores, | ||
* '''yscrs''' = Y-block scores, and | * '''yscrs''' = Y-block scores, and | ||
* '''basis''' = the basis of X-block loadings. | * '''basis''' = the basis of X-block loadings. | ||
Note: The regression matrices are ordered in reg such that each ''Ny'' (number of Y-block variables) rows correspond to the regression matrix for that particular number of latent variables. | '''Note:''' The regression matrices are ordered in reg such that each ''Ny'' (number of Y-block variables) rows correspond to the regression matrix for that particular number of latent variables. | ||
NOTE: in previous versions of SIMPLS, the X-block scores were unit length and the X-block loadings contained the variance. As of Version 3.0, this algorithm now uses standard convention in which the X-block scores contain the variance. | '''NOTE:''' in previous versions of SIMPLS, the X-block scores were unit length and the X-block loadings contained the variance. As of Version 3.0, this algorithm now uses standard convention in which the X-block scores contain the variance. | ||
===Options=== | ===Options=== | ||
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* '''display''': [ {'on'} | 'off' ], governs level of display, and | * '''display''': [ {'on'} | 'off' ], governs level of display, and | ||
* '''ranktest''': [ 'none' | 'data' | 'scores' | {'auto'} ], governs type of rank test to perform. | * '''ranktest''': [ 'none' | 'data' | 'scores' | {'auto'} ], governs type of rank test to perform. | ||
:: ''''data'''' = single test on X-block (faster with smaller data blocks and more components), | |||
:: ''''scores'''' = test during regression on scores matrix (faster with larger data matricies), | |||
:: ''''auto'''' = automatic selection, or | |||
:: ''''none'''' = assumes X-block has sufficient rank. | |||
===See Also=== | ===See Also=== | ||
[[crossval]], [[modelstruct]], [[pcr]], [[plsnipal]], [[preprocess]], [[analysis]] | [[crossval]], [[modelstruct]], [[pcr]], [[plsnipal]], [[preprocess]], [[analysis]] | ||
Revision as of 12:34, 9 October 2008
Purpose
Partial Least Squares regression using the SIMPLS algorithm.
Synopsis
- [reg,ssq,xlds,ylds,wts,xscrs,yscrs,basis] = simpls(x,y,ncomp,options)
Description
SIMPLS performs PLS regression using SIMPLS algorithm.
Inputs
- x = X-block (predictor block) class "double" or "dataset", and
- y = Y-block (predicted block) class "double" or "dataset".
Optional Inputs
- ncomp = integer, number of latent variables to use in {default = rank of X-block}, and
- options = a structure array discussed below.
Outputs
- reg = matrix of regression vectors,
- ssq = the sum of squares captured (ssq),
- xlds = X-block loadings,
- ylds = Y-block loadings,
- wts = X-block weights,
- xscrs = X-block scores,
- yscrs = Y-block scores, and
- basis = the basis of X-block loadings.
Note: The regression matrices are ordered in reg such that each Ny (number of Y-block variables) rows correspond to the regression matrix for that particular number of latent variables.
NOTE: in previous versions of SIMPLS, the X-block scores were unit length and the X-block loadings contained the variance. As of Version 3.0, this algorithm now uses standard convention in which the X-block scores contain the variance.
Options
options = a structure array with the following fields:
- display: [ {'on'} | 'off' ], governs level of display, and
- ranktest: [ 'none' | 'data' | 'scores' | {'auto'} ], governs type of rank test to perform.
- 'data' = single test on X-block (faster with smaller data blocks and more components),
- 'scores' = test during regression on scores matrix (faster with larger data matricies),
- 'auto' = automatic selection, or
- 'none' = assumes X-block has sufficient rank.