# #' A PCADSC object
# #'
# #' Blabla
# #'
# #' @slot pcaFrame ...
# #' @slot splitBy ...
# #' @slot splitLevels ...
# #' @slot varNames ...
# #' @slot n1 ...
# #' @slot n2 ...
# #' @slot nObs1 ...
# #' @slot nObs2 ...
# #'
# #' @examples
# #' #load iris data
# #' data(iris)
# #'
# #' #Define grouping variable, grouping the observations by whether their species is
# #' #Setosa or not
# #' iris$group <- "setosa"
# #' iris$group[iris$Species != "setosa"] <- "non-setosa"
# #'
# #' #make a PCADSC object, splitting the data by "group"
# #' irisPCADSC <- makePCADSC(iris, "group",
# #' var=setdiff(names(iris), c("group", "Species")))
# #' #plot it
# #' qplot(irisPCADSC)
# #'
# #' #print it
# #' print(irisPCADSC)
# #'
# #'
# #'
# #' @importFrom methods setClass new
# #' @export
# PCADSC <- setClass("PCADSC",
# slots = list(pcaFrame = "data.frame", splitBy = "character",
# splitLevels = "character", varNames = "character",
# n1 = "numeric", n2 = "numeric", nObs1 = "numeric",
# nObs2 = "numeric"))
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