Mlr: Difference between revisions

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* '''plots''': [ 'none' | {'final'} ]  governs level of plotting.
* '''plots''': [ 'none' | {'final'} ]  governs level of plotting.
* '''ridge''': [ 0 ] ridge parameter to use in regularizing the inverse.


* '''preprocessing''':  { [] [] } preprocessing structure (see PREPROCESS).
* '''preprocessing''':  { [] [] } preprocessing structure (see PREPROCESS).

Revision as of 10:32, 10 June 2014

Purpose

Multiple Linear Regression for multivariate Y.

Synopsis

model = mlr(x,y,options)
pred = mlr(x,model,options)
valid = mlr(x,y,model,options)

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' ] Extent of predictions and raw residuals included in model. 'standard' = only y-block, 'all' x and y blocks.

See Also

analysis, crossval, ils_esterror, modelstruct, pcr, pls, preprocess, ridge, testrobustness