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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