OSOAs_hadamard {SOAs} | R Documentation |
function to create a strength 3 OSOA with 8-level columns or a strength 3- OSOA with 4-level columns from a Hadamard matrix
Description
A Hadamard matrix in k runs is used for creating an OSOA in n=2k runs for at most m=k-2 columns (8-level) or m=k-1 columns (4-level).
Usage
OSOAs_hadamard(
m = NULL,
n = NULL,
el = 3,
noptim.rounds = 1,
noptim.repeats = 1,
optimize = TRUE,
dmethod = "manhattan",
p = 50
)
Arguments
m |
the number of columns to be created;
if |
n |
the number of runs to be created; |
el |
exponent for 2, can be 2 or 3: the OSOA will have columns with
2^ |
noptim.rounds |
the number of optimization rounds for each independent restart |
noptim.repeats |
the number of independent restarts of optimizations with |
optimize |
logical: should space filling be optimized by level permutations? |
dmethod |
distance method for |
p |
p for |
Details
At least one of m
or n
must be provided. For el=2
,
Zhou and Tang (2019) strength 3- designs are created, for el=3
strength
3 designs by Li, Liu and Yang (2021).
Li et al.'s creation of the matrix A has been enhanced by using a column specific
fold-over, which is beneficial for the space-filling properties (see Groemping 2022).
Value
matrix of class SOA
with the attributes that are listed below. All attributes can be accessed using function attributes
, or individual attributes can be accessed using function attr
. These are the attributes:
- type
the type of array (
SOA
orOSOA
)- strength
character string that gives the strength
- phi_p
the phi_p value (smaller=better)
- optimized
logical indicating whether optimization was applied
- permpick
matrix that lists the id numbers of the permutations used
- perms2pickfrom
optional element, when optimization was conducted: the overall permutation list to which the numbers in permlist refer
- call
the call that created the object
Author(s)
Ulrike Groemping
References
For full detail, see SOAs-package
.
Groemping (2023a)
Li, Liu and Yang (2021)
Weng (2014)
Zhou and Tang (2019)
Examples
dim(OSOAs_hadamard(9, optimize=FALSE)) ## 9 8-level factors in 24 runs
dim(OSOAs_hadamard(n=16, optimize=FALSE)) ## 6 8-level factors in 16 runs
OSOAs_hadamard(n=24, m=6, optimize=FALSE) ## 6 8-level factors in 24 runs
## (though 10 would be possible)
dim(OSOAs_hadamard(m=35, optimize=FALSE)) ## 35 8-level factors in 80 runs