bbd.design | R Documentation |
Function for generating Box-Behnken designs, making use of package rsm
bbd.design(nfactors, ncenter=4, factor.names = NULL, default.levels=c(-1,1),
block.name=NULL, randomize=TRUE, seed=NULL, ...)
nfactors |
number of factors |
ncenter |
integer number of center points for each block |
factor.names |
list of scale end values for each factor
(the middle value is calculated); |
default.levels |
default levels (vector of length 2) for all factors for which no specific levels are given; must consist of two numeric values for the scale ends, the default middle level is calculated |
block.name |
name of block factor that distinguishes between the blocks;
blocks are usable for nfactors=4 and nfactors=5 only, |
randomize |
logical that indicates whether or not randomization should occur |
seed |
optional seed for random number generation in randomization |
... |
reserved for future usage |
Function bbd.design
creates a Box-Behnken design, which is a design for quantitative
factors with all factors on three levels. Box-Behnken designs should not be used if the combinations
of the extreme levels of the factors are of interest (cf. also Myers, Montgomery and Anderson-Cook 2009).
There are designs for 3 to 7 factors, and the unreplicated versions of these have
14 (3 factors), 24 (4 factors), 40 (5 factors), 48 (6 factors), and 56 (7 factors) runs
plus the specified number of center points ncenter
.
Function bbd.design
is an interface to function bbd
from package rsm
that makes this design accessible using similar syntax as used in packages DoE.base and FrF2
and creates an output object that is also treatable by the convenience functions available in package
DoE.base.
Currently, creation of replications and repeated measurements - as would be usual for other design functions - is not implemented. This is planned for the future, but does not have high priority.
The function returns a data frame of S3 class design
with attributes attached. The data frame itself is in the original data scale.
The matrix desnum
attached as attribute desnum
contains the coded data,
the attribute run.order
contains the standard order and the actual run order
of the design (contrary to package rsm
, the row names of the design refer to
the actual rather than the standard run order).
The attribute design.info
is a list of design properties.
The element type
of that list is the character string bbd
.
Besides the elements present in all class design
objects,
there are the elements quantitative (vector with nfactor
TRUE entries),
and a codings
element usable in the coding functions available in the rsm
package, e.g. coded.data
.
Since R version 3.6.0, the behavior of function sample
has changed
(correction of a biased previous behavior that should not be relevant for the randomization of designs).
For reproducing a randomized design that was produced with an earlier R version,
please follow the steps described with the argument seed
.
This package is still under (slow) development. Reports about bugs and inconveniences are welcome. bbd.design
is based on version 1 of package rsm.
Ulrike Groemping
Box, G.E.P. and Behnken, D.W. (1960). Some new three-level designs for the study of quantitative variables. Technometrics 2, 455-475.
Box, G.E.P., Hunter, J.S. and Hunter, W.G. (2005, 2nd ed.). Statistics for Experimenters. Wiley, New York.
Box, G.E.P. and Wilson, K.B. (1951). On the Experimental Attainment of Optimum Conditions. J. Royal Statistical Society, B13, 1-45.
NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/pri/section3/pri3361.htm, accessed August 20th, 2009.
Myers, R.H., Montgomery, D.C. and Anderson-Cook, C.M. (2009). Response Surface Methodology. Process and Product Optimization Using Designed Experiments. Wiley, New York.
See also FrF2
, ccd.design
, lhs-package
, rsm
plan1 <- bbd.design(5) ## default for 5 factors is unblocked design, contrary to package rsm
plan1
## blocked design for 4 factors, using default levels
plan2 <- bbd.design(4,block.name="block",default.levels=c(10,30))
plan2
desnum(plan2)
## design with factor.names and modified ncenter
bbd.design(3,ncenter=6,
factor.names=list("one"=c(25,35),"two"=c(-5,20), "three"=c(20,60)))
## design with character factor.names and default levels
bbd.design(3,factor.names=c("one","two", "three"), default.levels=c(10,20))
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