Difference between revisions of "Npls"

From Eigenvector Research Documentation Wiki
Jump to navigation Jump to search
imported>Jeremy
(Importing text file)
imported>Jeremy
(Importing text file)
Line 1: Line 1:
 +
 
===Purpose===
 
===Purpose===
 +
 
Multilinear-PLS (N-PLS) for true multi-way regression.
 
Multilinear-PLS (N-PLS) for true multi-way regression.
 +
 
===Synopsis===
 
===Synopsis===
 +
 
:model = npls(x,y,ncomp,''options'')
 
:model = npls(x,y,ncomp,''options'')
 +
 
:pred  = npls(x,ncomp,model,''options'')
 
:pred  = npls(x,ncomp,model,''options'')
 +
 
:options = npls('options')
 
:options = npls('options')
 +
 
===Description===
 
===Description===
 +
 
NPLS fits a multilinear PLS1 or PLS2 regression model to x and y [R. Bro, J. Chemom., 1996, 10(1), 47-62]. The NPLS function also can be used for calibration and prediction.
 
NPLS fits a multilinear PLS1 or PLS2 regression model to x and y [R. Bro, J. Chemom., 1996, 10(1), 47-62]. The NPLS function also can be used for calibration and prediction.
 +
 
====INPUTS====
 
====INPUTS====
 +
 
* '''x''' = X-block,
 
* '''x''' = X-block,
 +
 
* '''y''' = Y-block, and
 
* '''y''' = Y-block, and
 +
 
* '''ncomp''' = the number of factors to compute, or
 
* '''ncomp''' = the number of factors to compute, or
 +
 
* '''model''' = in prediction mode, this is a structure containing a NPLS model.
 
* '''model''' = in prediction mode, this is a structure containing a NPLS model.
 +
 
====OPTIONAL INPUTS====
 
====OPTIONAL INPUTS====
 +
 
*'''''''' options'' = discussed below.
 
*'''''''' options'' = discussed below.
 +
 
====OUTPUTS====
 
====OUTPUTS====
 +
 
* '''model''' = standard model structure (see: MODELSTRUCT) with the following fields:
 
* '''model''' = standard model structure (see: MODELSTRUCT) with the following fields:
 +
 
* '''modeltype''': 'NPLS',
 
* '''modeltype''': 'NPLS',
 +
 
* '''datasource''': structure array with information about input data,
 
* '''datasource''': structure array with information about input data,
 +
 
* '''date''': date of creation,
 
* '''date''': date of creation,
 +
 
* '''time''': time of creation,
 
* '''time''': time of creation,
 +
 
* '''info''': additional model information,
 
* '''info''': additional model information,
 +
 
* '''reg''': cell array with regression coefficients,
 
* '''reg''': cell array with regression coefficients,
 +
 
* '''loads''': cell array with model loadings for each mode/dimension,
 
* '''loads''': cell array with model loadings for each mode/dimension,
 +
 
* '''core''': cell array with the NPLS core,
 
* '''core''': cell array with the NPLS core,
 +
 
* '''pred''': cell array with model predictions for each input data block,
 
* '''pred''': cell array with model predictions for each input data block,
 +
 
* '''tsqs''': cell array with T<sup>2</sup> values for each mode,
 
* '''tsqs''': cell array with T<sup>2</sup> values for each mode,
 +
 
* '''ssqresiduals''': cell array with sum of squares residuals for each mode,
 
* '''ssqresiduals''': cell array with sum of squares residuals for each mode,
 +
 
* '''description''': cell array with text description of model, and
 
* '''description''': cell array with text description of model, and
 +
 
* '''detail''': sub-structure with additional model details and results.
 
* '''detail''': sub-structure with additional model details and results.
 +
 
===Options===
 
===Options===
 +
 
* '''''options''''' = options structure containing the fields:
 
* '''''options''''' = options structure containing the fields:
 +
 
* '''display''': [ 'off' | {'on'} ], governs level of display to command window,
 
* '''display''': [ 'off' | {'on'} ], governs level of display to command window,
 +
 
* '''plots''': [ 'none' | {'final'} ], governs level of plotting,
 
* '''plots''': [ 'none' | {'final'} ], governs level of plotting,
 +
 
* '''outputregrescoef''':  if this is set to 0 no regressions coefficients associated with the X-block directly are calculated (relevant for large arrays), and
 
* '''outputregrescoef''':  if this is set to 0 no regressions coefficients associated with the X-block directly are calculated (relevant for large arrays), and
 +
 
* '''blockdetails''': [ {'standard'} | 'all' ], level of detail included in the model for predictions and residuals.
 
* '''blockdetails''': [ {'standard'} | 'all' ], level of detail included in the model for predictions and residuals.
 +
 
===See Also===
 
===See Also===
 +
 
[[datahat]], [[explode]], [[gram]], [[mpca]], [[outerm]], [[parafac]], [[pls]], [[tld]], [[unfoldm]]
 
[[datahat]], [[explode]], [[gram]], [[mpca]], [[outerm]], [[parafac]], [[pls]], [[tld]], [[unfoldm]]

Revision as of 15:26, 3 September 2008

Purpose

Multilinear-PLS (N-PLS) for true multi-way regression.

Synopsis

model = npls(x,y,ncomp,options)
pred = npls(x,ncomp,model,options)
options = npls('options')

Description

NPLS fits a multilinear PLS1 or PLS2 regression model to x and y [R. Bro, J. Chemom., 1996, 10(1), 47-62]. The NPLS function also can be used for calibration and prediction.

INPUTS

  • x = X-block,
  • y = Y-block, and
  • ncomp = the number of factors to compute, or
  • model = in prediction mode, this is a structure containing a NPLS model.

OPTIONAL INPUTS

  • ''' options = discussed below.

OUTPUTS

  • model = standard model structure (see: MODELSTRUCT) with the following fields:
  • modeltype: 'NPLS',
  • datasource: structure array with information about input data,
  • date: date of creation,
  • time: time of creation,
  • info: additional model information,
  • reg: cell array with regression coefficients,
  • loads: cell array with model loadings for each mode/dimension,
  • core: cell array with the NPLS core,
  • pred: cell array with model predictions for each input data block,
  • tsqs: cell array with T2 values for each mode,
  • ssqresiduals: cell array with sum of squares residuals for each mode,
  • description: cell array with text description of model, and
  • detail: sub-structure with additional model details and results.

Options

  • options = options structure containing the fields:
  • display: [ 'off' | {'on'} ], governs level of display to command window,
  • plots: [ 'none' | {'final'} ], governs level of plotting,
  • outputregrescoef: if this is set to 0 no regressions coefficients associated with the X-block directly are calculated (relevant for large arrays), and
  • blockdetails: [ {'standard'} | 'all' ], level of detail included in the model for predictions and residuals.

See Also

datahat, explode, gram, mpca, outerm, parafac, pls, tld, unfoldm