Mlr
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Contents |
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.
- 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