Rinverse: Difference between revisions

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===Purpose===
===Purpose===


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===Synopsis===
===Synopsis===


:rinv = rinverse(mod,ncomp)
:rinv = rinverse(mod,ncomp) % for PLS or PCR model structures
:rinv = rinverse(p,t,w,ncomp)
:rinv = rinverse(p,t,w,ncomp) % for PLS
:rinv = rinverse(p,t,ncomp)
:rinv = rinverse(p,t,ncomp)   % for PCR
:rinv = rinverse(sx,theta)
:rinv = rinverse(sx,theta)   % for RR


===Description===
===Description===


For the following I/O format:
This function calculates the pseudo-inverse of a PLS, PCR or Ridge Regression (RR) model, using either a standard model structure, or a series of model parameter arrays. There are four different input cases, depending on the type of model, and whether a standard model structure exists:
 
:rinv = rinverse(mod,ncomp)


The input mod is a model structure from PCR, PLS, or ANALYSIS and ncomp is the number of factors in the model (number of principal components or latent variables).
====Input Cases====


For PLS models, the inputs are the loadings p, scores t, weights w and number of latent variables ncomp. For this case the I/O syntax is:
* For PLS and PCR model structures, the inputs are the model <tt>mod</tt>) and the optional number of factors <tt>ncomp</tt>.
:rinv = rinverse(mod,ncomp);


rinv = rinverse(p,t,w,ncomp)
* For PLS models, the inputs are the loadings <tt>p</tt>, scores <tt>t</tt>, weights <tt>w</tt> and number of LVs <tt>ncomp</tt>.


For PCR models, the inputs are the loadings p, scores t, and number of principal components ncomp. For this case the I/O syntax is:
:rinv = rinverse(p,t,w,ncomp);


rinv = rinverse(p,t,ncomp)
* For PCR models, the inputs are the loadings <tt>p</tt>, scores <tt>t</tt>, and number of PCs <tt>ncomp</tt>.
:rinv = rinverse(p,t,ncomp);


For ridge regression (RR) models, the inputs are the scaled predictor x matrix sx and ridge parameter theta.
* For ridge regression (RR) models, the inputs are the scaled x matrix <tt>sx</tt> and ridge parameter <tt>theta</tt>.
:rinv = rinverse(sx,theta).
====Outputs====


rinv = rinverse(sx,theta)
* '''rinv''' = pseudo-inverse of model


===See Also===
===See Also===


[[pcr]], [[pls]], [[ridge]], [[stdsslct]]
[[pcr]], [[pls]], [[ridge]], [[stdsslct]]

Revision as of 10:24, 9 October 2008

Purpose

Calculates pseudo inverse for PLS, PCR and RR models.

Synopsis

rinv = rinverse(mod,ncomp)  % for PLS or PCR model structures
rinv = rinverse(p,t,w,ncomp)  % for PLS
rinv = rinverse(p,t,ncomp)  % for PCR
rinv = rinverse(sx,theta)  % for RR

Description

This function calculates the pseudo-inverse of a PLS, PCR or Ridge Regression (RR) model, using either a standard model structure, or a series of model parameter arrays. There are four different input cases, depending on the type of model, and whether a standard model structure exists:

Input Cases

  • For PLS and PCR model structures, the inputs are the model mod) and the optional number of factors ncomp.
rinv = rinverse(mod,ncomp);
  • For PLS models, the inputs are the loadings p, scores t, weights w and number of LVs ncomp.
rinv = rinverse(p,t,w,ncomp);
  • For PCR models, the inputs are the loadings p, scores t, and number of PCs ncomp.
rinv = rinverse(p,t,ncomp);
  • For ridge regression (RR) models, the inputs are the scaled x matrix sx and ridge parameter theta.
rinv = rinverse(sx,theta).

Outputs

  • rinv = pseudo-inverse of model

See Also

pcr, pls, ridge, stdsslct