# Difference between revisions of "Npls"

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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 20:57, 2 September 2008

## 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