Mlr

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