Statistics Toolbox™

ccdesign - Central composite design

Syntax

dCC = ccdesign(n)
[dCC,blocks] = ccdesign(n)
[...] = ccdesign(n,param1,val1,param2,val2,...)

Description

dCC = ccdesign(n) generates a central composite design for n factors. n must be an integer 2 or larger. The output matrix dCC 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.

[dCC,blocks] = ccdesign(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.

[...] = ccdesign(n,param1,val1,param2,val2,...) specifies additional parameter/value pairs for the design. Valid parameters and their values are listed in the following table.

Example

The following creates a 2-factor CCC:

dCC = ccdesign(2,'type','circumscribed')
dCC =
   -1.0000   -1.0000
   -1.0000    1.0000
    1.0000   -1.0000
    1.0000    1.0000
   -1.4142         0
    1.4142         0
         0   -1.4142
         0    1.4142
         0         0
         0         0
         0         0
         0         0
         0         0
         0         0
         0         0
         0         0

The center point is run 8 times to allow for a more uniform estimate of the prediction variance over the entire design space.

Visualize the design as follows:

plot(dCC(:,1),dCC(:,2),'ro','MarkerFaceColor','b')
X = [1 -1 -1 -1; 1 1 1 -1];
Y = [-1 -1 1 -1; 1 -1 1 1];
line(X,Y,'Color','b')
axis square equal

See Also

bbdesign

casewrite

cdf