grpWV: Produce a grpWV object
In ziyanyin/DEEE: DE EE Analysis

Description Usage Arguments Value Examples

grpWV defines and produces a grpWV object. The difference between grpWV and weave is their way to apply FUN. In weave, FUN is applied to every single column; while in grpWV, FUN takes the whole columns in a group as argument. See also madWV, in which a grpWV object also is produced, but with FUN = “mad”, interval = c(0, 1) and ifeq = “>”. See plot.grpWV for plotting instructions.

1	grpWV(SVobj, degree = 6, interval = c(0, 1), FUN = "mad", ifeq = FALSE)

`SVobj`	A samVec object containing data and other information.
`degree`	A integer specifying the degree of the polynomail logistic regression that applied to fit the data.
`interval`	A value between 0 and 1 to restrict the rankit used.
`FUN`	A string specifying the function used in grpWV.
`ifeq`	An bool value indicating whether >= or > is used in comparison. This argument is only valid when it comes tied values.

A grpWV object is returned, which is a list containing

fitY: A list of lists of numerics containing the fitted response values.
rankit: A list of numerics containing the rankit of the means of the data matrix.
order: A list of integers containing the order the rankit.
nWV: An integers indicating the numbers of grpWV.
interval: An interval indicating the range of rankit that is used.
Function: A string indicating the function used in grpWV.
ifeq: An bool value indicating whether >= or > is used in comparison. This argument is only valid when it comes tied values.
selCol: A list of vector of integers containing absolute indexes of choosen columns.
colInd: A list of vector of integers containing relative indexes of columns.
labels: A vector of characters, integers or short string marking the groups.
dataType: A long string containing useful information of the data.

data(GCwPADataA)
t1 = samVec(GCwPADataA, selCol = list(1:5, 11:15, 21:25), labels = c("E", "R", "T"),
 dataType = "Example")
madRes = grpWV(SVobj = t1, degree = 6, interval = c(0, 1), FUN = "mad", ifeq = TRUE)
plot(madRes, legPar = list(cex = 1, ncol = 1), mainPar = list(main = "Example"))