Statistics Toolbox

daugment

D-optimal augmentation of an experimental design.

Syntax

settings = daugment(startdes,nruns)
[settings,X] = daugment(startdes,nruns,'model')

Description

settings = daugment(startdes,nruns) augments an initial experimental design, startdes, with nruns new tests.

[settings,X] = daugment(startdes,nruns,'model') also supplies the design matrix, X. The input, 'model', controls the order of the regression model. By default, daugment assumes a linear additive model. Alternatively, 'model' can be any of these:

• 'interaction' - includes constant, linear, and cross product terms.
• 'quadratic' - includes interactions plus squared terms.
• 'purequadratic' - includes constant, linear, and squared terms.

daugment uses the coordinate exchange algorithm.

Example

We add 5 runs to a 2² factorial design to allow us to fit a quadratic model.

startdes = [-1 -1; 1 -1; -1 1; 1 1];
settings = daugment(startdes,5,'quadratic')
settings =
    -1    -1
     1    -1
    -1     1
     1     1
     1     0
    -1     0
     0     1
     0     0
     0    -1

The result is a 3² factorial design.

See Also
cordexch, dcovary, rowexch

crosstab

dcovary