Calculates GWLP using the formulae from Xu and Wu (2001)
GWLP(design, ...)
# S3 method for design
GWLP(design, kmax=design.info(design)$nfactors,
attrib.out=FALSE, with.blocks = FALSE, digits = NULL, ...)
# S3 method for default
GWLP(design, kmax=ncol(design), attrib.out=FALSE, digits = NULL, ...)The GWLP methods output a named vector with the numbers of generalized
words of lengths zero to kmax. If attrib.out is TRUE,
this vector comes with the attributes B and levels.info,
the latter documenting the level situation of the design, the former
the distance distribution B (Xu and Wu 2001).
a design, not necessarily of class design;
class design properties are exploited by using only factor columns
(or factor and block columns, if with.blocks is TRUE)
the maximum word length requested
the detail added to the output (see Value section)
if TRUE, the block column contributes to
the GWLP, otherwise it does not
the number of decimals to round to; NULL prevents rounding
further arguments to generic GWLP; not used in the methods
Hongquan Xu, Ulrike Groemping
Function GWLP is much faster but also more inaccurate than the
function lengths, which calculates numbers of words
for lengths 2 to 5 only. Note, however, that function lengths
can be faster for designs with very many rows.
If a design factor contains only some of the intended levels,
design must be a data frame, and the factor must be an R
factor with the complete set of levels specified,
in order to make function GWLP aware of the missing levels.
Xu, H.-Q. and Wu, C.F.J. (2001). Generalized minimum aberration for asymmetrical fractional factorial designs. Annals of Statistics 29, 1066--1077.
See Also lengths
GWLP(L18)
GWLP(L18, attrib.out=TRUE)
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