Plsnipal: Difference between revisions

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===Purpose===
===Purpose===
Calculate single latent variables for partial least squares regression.
 
Calculate a single latent variable for partial least squares (PLS) regression.
 
===Synopsis===
===Synopsis===
:[p,q,w,t,u] = plsnipal(x,y)
:[p,q,w,t,u] = plsnipal(x,y)
===Description===
===Description===
PLSNIPAL is called by the routine pls to calculate each latent variable in a partial least squares regression.
 
Inputs x and y are either the x-block and y-block for calculation of the first latent variable, or the x-block and y-block residuals for calculation of subsequent latent variables.
PLSNIPAL is called by the routine [[pls]] to calculate each latent variable in a partial least squares regression.
The outputs are p the x-block latent variable loadings, q the y-block variable loadings, w the x-block latent variable weights, t the x-block latent variable scores, and u the y-block latent variable scores.
 
====Inputs====
 
* '''x''' = x-block input data (for first PLS latent variable), or x-block residuals (for subsequent latent variables)
* '''y''' = y-block input data (for first PLS latent variable), or y-block residuals (for subsequent latent variables)
 
====Outputs====
 
* '''p''' = x-block latent variable loadings  
* '''q''' = y-block latent variable loadings
* '''w''' = x-block latent variable weights
* '''t''' = x-block latent variable scores
* '''u''' = y-block latent variable scores
 
===See Also===
===See Also===
[[nippls]], [[pls]], [[analysis]], [[simpls]]
 
[[analysis]], [[dspls]], [[nippls]], [[pls]], [[simpls]]

Latest revision as of 15:53, 21 September 2011

Purpose

Calculate a single latent variable for partial least squares (PLS) regression.

Synopsis

[p,q,w,t,u] = plsnipal(x,y)

Description

PLSNIPAL is called by the routine pls to calculate each latent variable in a partial least squares regression.

Inputs

  • x = x-block input data (for first PLS latent variable), or x-block residuals (for subsequent latent variables)
  • y = y-block input data (for first PLS latent variable), or y-block residuals (for subsequent latent variables)

Outputs

  • p = x-block latent variable loadings
  • q = y-block latent variable loadings
  • w = x-block latent variable weights
  • t = x-block latent variable scores
  • u = y-block latent variable scores

See Also

analysis, dspls, nippls, pls, simpls