fac.design {DoE.base}R Documentation

Function for full factorial designs

Description

Function for creating full factorial designs with arbitrary numbers of levels

Usage

fac.design(nlevels=NULL, nfactors=NULL, factor.names = NULL, 
        replications=1, repeat.only = FALSE, randomize=TRUE, seed=NULL)

Arguments

nlevels number(s) of levels, vector with nfactors entries or single number; can be omitted, if obvious from factor.names
nfactors number of factors, can be omitted if obvious from entries nlevels or factor.names
factor.names if nlevels is given, factor.names can be a character vector of factor names. Otherwise it must be a named list of vectors with factor levels. If both nlevels and factor.names are given, they must be compatible.
replications positive integer number. Default 1 (i.e. each row just once). If larger, each design run is executed replication times. If repeat.only, repeated measurements are carried out directly in sequence, i.e. no true replication takes place, and all the repeat runs are conducted together. It is likely that the error variation generated by such a procedure will be too small, so that average values should be analyzed for an unreplicated design.
Otherwise (default), the full experiment is first carried out once, then for the second replication and so forth. In case of randomization, each such blocks is randomized separately. In this case, replication variance is more likely suitable for usage as error variance (unless e.g. the same parts are used for replication runs although build variation is important).
repeat.only logical, relevant only if replications > 1. If TRUE, replications of each run are grouped together (repeated measurement rather than true replication). The default is repeat.only=FALSE, i.e. the complete experiment is conducted in replications blocks, and each run occurs in each block.
randomize logical. If TRUE, the design is randomized. This is the default. In case of replications, the nature of randomization depends on the setting of option repeat.only.
seed optional seed for the randomization process

Details

fac.design creates full factorial designs, i.e. the number of runs is the product of all numbers of levels.

Value

fac.design returns a data frame of S3 class design with attributes attached.

Note

This package is currently under intensive development. Substantial changes are to be expected in the near future.

Author(s)

Ulrike Groemping

References

Hedayat, A.S., Sloane, N.J.A. and Stufken, J. (1999) Orthogonal Arrays: Theory and Applications, Springer, New York.

See Also

~~See Also FrF2, oa.design, pb


[Package DoE.base version 0.2 Index]