# Npls

Revision as of 20:57, 2 September 2008 by imported>Jeremy (Importing text file)

## Contents

### 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 T^{2}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 structure containing the fields:**options****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