Box-Behnken design
dBB = bbdesign(n)
[dBB,blocks] = bbdesign(n)
[...] = bbdesign(n,param,val)
dBB = bbdesign(n) generates
a Box-Behnken design for n factors. n must
be an integer 3 or larger. The output matrix dBB is m-by-n,
where m is the number of runs in the design. Each
row represents one run, with settings for all factors represented
in the columns. Factor values are normalized so that the cube points
take values between -1 and 1.
[dBB,blocks] = bbdesign(n) requests
a blocked design. The output blocks is an m-by-1
vector of block numbers for each run. Blocks indicate runs that are
to be measured under similar conditions to minimize the effect of
inter-block differences on the parameter estimates.
[...] = bbdesign(n, specifies
one or more optional parameter/value pairs for the design. The following
table lists valid parameter/value pairs.param,val)
| Parameter | Description | Values |
|---|---|---|
'center' | Number of center points. | Integer. The default depends on |
'blocksize' | Maximum number of points per block. | Integer. The default is |
The following creates a 3-factor Box-Behnken design:
dBB = bbdesign(3)
dBB =
-1 -1 0
-1 1 0
1 -1 0
1 1 0
-1 0 -1
-1 0 1
1 0 -1
1 0 1
0 -1 -1
0 -1 1
0 1 -1
0 1 1
0 0 0
0 0 0
0 0 0The center point is run 3 times to allow for a more uniform estimate of the prediction variance over the entire design space.
Visualize the design as follows:
plot3(dBB(:,1),dBB(:,2),dBB(:,3),'ro',...
'MarkerFaceColor','b')
X = [1 -1 -1 -1 1 -1 -1 -1 1 1 -1 -1; ...
1 1 1 -1 1 1 1 -1 1 1 -1 -1];
Y = [-1 -1 1 -1 -1 -1 1 -1 1 -1 1 -1; ...
1 -1 1 1 1 -1 1 1 1 -1 1 -1];
Z = [1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1; ...
1 1 1 1 -1 -1 -1 -1 1 1 1 1];
line(X,Y,Z,'Color','b')
axis square equal