Mlr: Difference between revisions
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* '''preprocessing''': { [] [] } preprocessing structure (see PREPROCESS). | * '''preprocessing''': { [] [] } preprocessing structure (see PREPROCESS). | ||
* '''blockdetails''': [ 'compact' | {'standard'} | 'all' ] | * '''blockdetails''': [ 'compact' | {'standard'} | 'all' ] level of detail (predictions, raw residuals, and calibration data) included in the model. | ||
:* ‘Compact’ - keep predictions, raw residuals and for y-block only (y-block included). | |||
:* ‘Standard’ - the default setting for this model: ‘Compact’. | |||
:* 'All' - keep predictions, raw residuals for both x & y blocks as well as the x & y blocks themselves. | |||
===See Also=== | ===See Also=== | ||
[[analysis]], [[crossval]], [[ils_esterror]], [[modelstruct]], [[pcr]], [[pls]], [[preprocess]], [[ridge]], [[testrobustness]] | [[analysis]], [[crossval]], [[ils_esterror]], [[modelstruct]], [[pcr]], [[pls]], [[preprocess]], [[ridge]], [[testrobustness]] | ||
Revision as of 13:38, 26 July 2017
Purpose
Multiple Linear Regression for multivariate Y.
Synopsis
- model = mlr(x,y,options)
- pred = mlr(x,model,options)
- valid = mlr(x,y,model,options)
- mlr % Launches analysis window with MLR as the selected method.
Description
MLR identifies models of the form Xb = y + e.
Inputs
- y = X-block: predictor block (2-way array or DataSet Object)
- y = Y-block: predictor block (2-way array or DataSet Object)
Outputs
- model = scalar, estimate of filtered data.
- pred = structure array with predictions
- valid = structure array with predictions
Options
options = a structure array with the following fields.
- display: [ {'off'} | 'on'] Governs screen display to command line.
- plots: [ 'none' | {'final'} ] governs level of plotting.
- ridge: [ 0 ] ridge parameter to use in regularizing the inverse.
- preprocessing: { [] [] } preprocessing structure (see PREPROCESS).
- blockdetails: [ 'compact' | {'standard'} | 'all' ] level of detail (predictions, raw residuals, and calibration data) included in the model.
- ‘Compact’ - keep predictions, raw residuals and for y-block only (y-block included).
- ‘Standard’ - the default setting for this model: ‘Compact’.
- 'All' - keep predictions, raw residuals for both x & y blocks as well as the x & y blocks themselves.
See Also
analysis, crossval, ils_esterror, modelstruct, pcr, pls, preprocess, ridge, testrobustness