cross.design | R Documentation |
This function generates cartesian products of two or more experimental designs.
cross.design(design1, design2, ..., randomize = TRUE, seed=NULL)
design1 |
a data frame of class if |
design2 |
a data frame of class |
... |
optional further data frames that are to be crossed;
they must be of class |
randomize |
logical indicating whether randomization should take place after crossing the designs |
seed |
integer seed for the random number generator |
Crossing is carried out recursively, following the direct.sum
approach
from package conf.design. All but the last designs must fulfill various
criteria (cf. below). The last design to be crossed can also be a vector.
Designs to be crossed must not be a blocked, nor splitplot, nor crossed, folded
or Taguchi parameter design, nor designs in wide format. Furthermore, designs must
not contain responses (checked via the response.names element of design.info
).
If replications are desired, it is recommended to accomodate them in the last
design. Only the last design may have repeat.only
replications. If the
last design has repeat.only
replications and there are also proper replications
in earlier designs, a warning is thrown, but the repeat.only
replications are
nevertheless accomodated; this is experimental and may not yield the expected
results under all circumstances.
Function cross.design
returns a simple data frame without design
information, if design1
is not of class design
.
Otherwise, the value is a data frame of class design
with type “crossed” and the following extraordinary elements:
cross.nruns |
vector of run numbers of individual designs |
cross.nfactors |
vector of numbers of factors of individual designs |
cross.types |
vector of types of individual designs |
cross.randomize |
vector of logicals (randomized or not) of individual desigs |
cross.seed |
vector of seeds of individual designs |
cross.replications |
vector of numbers of replications of individual designs |
cross.repeat.only |
vector of logicals (repeat.only or not) of individual designs |
cross.map |
list with the map vectors for component designs of type |
cross.selected.columns |
|
cross.nlevels |
list with the |
The standard elements are as usual, with randomize
and seed
referring to
the randomization within function cross.design
itself (previous randomizations are shown
under cross.randomize
and cross.seed
).
The nlevels
element of design.info
is available only if it is
available for all designs that have been crossed (otherwise refer to the element cross.nlevels
.
The creator
element of the design.info
attribute consists is a 2-element list
containing
the list original
of all the original creators and
the element modify
that contains the call to cross.design
.
If present, the clear
, ncube
, ncenter
, residual.df
,
origin
, comment
, generating.oa
elements of design.info
are vector-valued.
If present, the generators
element of design.info
is a list of character vectors.
If present, the aliased
and catlg.entry
elements of design.info
are lists of lists.
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 function is still experimental.
Ulrike Groemping
See Also param.design
## creating a Taguchi-style inner-outer array design
## with proper randomization
## function param.design would generate such a design with all outer array runs
## for each inner array run conducted in sequence
## alternatively, a split-plot approach can also handle control and noise factor
## designs without necessarily crossing two separate designs
des.control <- oa.design(ID=L18)
des.noise <- oa.design(ID=L4.2.3,nlevels=2,factor.names=c("N1","N2","N3"))
crossed <- cross.design(des.control, des.noise)
crossed
summary(crossed)
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