Statistics Toolbox

rowexch

D-optimal design of experiments - row exchange algorithm.

Syntax

settings = rowexch(nfactors,nruns)
[settings,X] = rowexch(nfactors,nruns)
[settings,X] = rowexch(nfactors,nruns,'model')

Description

settings = rowexch(nfactors,nruns) generates the factor settings matrix, settings, for a D-Optimal design using a linear additive model with a constant term. settings has nruns rows and nfactors columns.

[settings,X] = rowexch(nfactors,nruns) also generates the associated design matrix X.

[settings,X] = rowexch(nfactors,nruns,'model') produces a design for fitting a specified regression model. The input, 'model', can be one of these strings:

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

Example

This example illustrates that the D-optimal design for three factors in eight runs, using an interactions model, is a two level full-factorial design.

s = rowexch(3,8,'interaction')
s =
    -1    -1     1
     1    -1    -1
     1    -1     1
    -1    -1    -1
    -1     1     1
     1     1     1
    -1     1    -1
     1     1    -1

See Also
cordexch, daugment, dcovary, fullfact, ff2n, hadamard

robustfit

rsmdemo