This function looks at all combinations of specified design parameters
for central-composite designs, calculates other quantities such as
alpha values for rotatability and orthogonal blocking, imposes
specified restrictions, and outputs the best combinations in a specified order.
This serves as an aid in identifying good designs. The design itself can
then be generated using
ccd, or in pieces using
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Number of factors in the design
Number(s) of factorial points in each cube block
Numbers(s) of center points in each cube block
Number(s) of cube blocks that together comprise one rep of the cube portion
Numbers(s) of center points in each star (axis-point) block
Number(s) of copies of each cube block
Number(s) of replications of each star poit within a block
Number(s) of copies of each star block
How many designs to list. Use
String(s) containing numeric expressions that are each evaluated and used as sorting key(s).
Optional string(s) containing Boolean expressions that are each evaluated. Only combinations where all
A grid is created with all combinations of
Then for each row of the grid, several additional variables
The total number of axis points in each star block
The total number of observations in the design
The position of axis points that make the design rotatable. Rotatability is achieved when design moment [iiii] = 3[iijj] for i and j unequal.
The position of axis points that make the blocks mutually orthogonal. This is achieved when design moments [ii] within each block are proprtional to the number of observations within the block.
The absolute value of the log of the ratio of
alpha.orth. This measures agreement between
restrict is provided, only the cases where the expressions are all
TRUE are kept.
restrict, rows are eliminated where there are
insufficient degrees of freedom to estimate all needed effects for a
The rows are
sorted according to the expressions in
sortby; the default is to sort
N, which is suitable for finding designs
that are both rotatable and orthogonally blocked.
best or fewer rows, and variables
as described above.
Russell V. Lenth
Lenth RV (2009) “Response-Surface Methods in R, Using rsm”, Journal of Statistical Software, 32(7), 1–17. http://www.jstatsoft.org/v32/i07/.
Myers, RH, Montgomery, DC, and Anderson-Cook, CM (2009) Response Surface Methodology (3rd ed.), Wiley.
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library(rsm) ### List CCDs in 3 factors with between 10 and 14 runs per block ccd.pick(3, n0.c=2:6, n0.s=2:8) # (Generate the design that is listed first:) # ccd(3, n0=c(6,4)) ### Find designs in 5 factors containing 1, 2, or 4 cube blocks ### of 8 or 16 runs, 1 or 2 reps of each axis point, ### and no more than 70 runs altogether ccd.pick(5, n.c=c(8,16), blks.c=c(1,2,4), wbr.s=1:2, restrict="N<=70")
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