Meta Model Interface: Linear Model

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Description

A linear prediction model, which will use higher order interactions if data is sufficient. Can be used both for single and multi objective SPOT.

Usage

1
spotPredictLm(rawB, mergedB, design, spotConfig, fit = NULL)

Arguments

rawB

unmerged data

mergedB

merged data

design

new design points which should be predicted

spotConfig

global list of all options, needed to provide data for calling functions

fit

if an existing model fit is supplied, the model will not be build based on data, but only evaluated with the model fit (on the design data). To build the model, this parameter has to be NULL. If it is not NULL the parameters mergedB and rawB will not be used at all in the function.

Details

This function implements a linear model for prediction. Depending on the numbers of variables either no interactions, interaction between the variables may be used or a full quadratic model is provided.

Value

returns the list spotConfig with two new entries:
spotConfig$seq.modelFit fit of the model used with predict()
spotConfig$seq.largeDesignY the y values of the design, evaluated with the fit

See Also

SPOT

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