aliases: Alias structure for fractional factorial 2-level designs

In FrF2: Fractional Factorial Designs with 2-Level Factors

Alias structure for fractional factorial 2-level designs

Description

Functions to examine the alias structure of a fractional factorial 2-level design

Usage

aliases(fit, code = FALSE, condense=FALSE)
aliasprint(design, ...)
## S3 method for class 'aliases'
print(x, ...)

Arguments

fit	a linear model object with only 2-level factors as explanatory variables; the function will return an error, if the model contains partially aliased effects (like interactions in a Plackett-Burman design for most cases)
code	if TRUE, requests that aliasing is given in code letters (A, B, C etc.) instead of (potentially lengthy) variable names; in this case, a legend is included in the output object.
condense	if TRUE, reformats the alias information to be comparable to the version calculated by internal function alias3fi; does not work with models with higher than 3-way interactions; for up to 3-way interactions, the output may be more easily readible
design	a data frame of class design that should contain a fractional factorial 2-level design; the function does not print anything if the design is of different nature
x	an object of class aliases that should be the output from function aliases
...	further arguments to function print.default; the quote argument cannot be used

Value

Function aliasprint returns NULL and is called for its side effects only.

Per default, Function aliases returns a list with two elements:

legend	links the codes to variable names, if code=TRUE.
aliases	is a list of vectors of aliased effects.

If option condense is TRUE, the function returns a list with elements legend, main, fi2 and fi3; this may be preferrable for looking at the alias structure of larger designs.

The output object of function aliases has class aliases, which is used for customized printing with the print method.

Author(s)

Ulrike Groemping

References

Box G. E. P, Hunter, W. C. and Hunter, J. S. (2005) Statistics for Experimenters, 2nd edition. New York: Wiley.

See Also

FrF2-package for information on the package, alias for the built-in R-function, IAPlot for effects plots

Examples

    ### Injection Molding Experiment. Box et al. 1978.
    ## data(BM93.e3.data, package="BsMD")  #from BsMD
    ## iMdat <- BM93.e3.data[1:16,2:10]  #only original experiment
    ## re-create here
    y=c(14, 16.8, 15, 15.4, 27.6, 24, 27.4, 22.6, 
     22.3, 17.1, 21.5, 17.5, 15.9, 21.9, 16.7, 20.3)
    iMdat <- FrF2(8,7,randomize=FALSE)
    iMdat <- desnum(iMdat)
    iMdat <- rbind(cbind(iMdat,H=1),cbind(-iMdat,H=-1))
    iMdat <- cbind(as.data.frame(iMdat), y=y)

    # make data more user-friendly
    colnames(iMdat) <- c("MoldTemp","Moisture","HoldPress","CavityThick",
             "BoostPress","CycleTime","GateSize","ScrewSpeed","y")
    # determine aliases with all 2-factor-interactions
    aliases(lm(y ~ (.)^2, data = iMdat))
    # coded version
    aliases(lm(y ~ (.)^2, data = iMdat), code=TRUE)
    # determine aliases with all 3-factor-interactions
    aliases(lm(y ~ (.)^3, data = iMdat), code=TRUE)
    # show condensed form
    aliases(lm(y ~ (.)^3, data = iMdat), code=TRUE, condense=TRUE)
    # determine aliases for unaliased model
    aliases(lm(y ~ ., data = iMdat))

FrF2 documentation built on Sept. 20, 2023, 9:08 a.m.