Npls: Difference between revisions
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===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==== | |||
* 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 19:57, 2 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