flip (version 2.5.0)

flip.object-class: Class flip.object

Description

The class flip.object is the output of a call to flip, flipMix, npc, flip.adjust etc. The following are functions to extract and manipulate relevant information from a flip.object.

show prints the flip.object.

summary: Prints information about the flip-object.

dim: Size of permutation space, i.e. the number of permutations X number of variables.

[ and [[: Extract parts of flip.object

names: it deals the names of the tests (the variables, usually)

sort: it sorts the tests stored in flip.objects by their p-values.

hist: it produces the histogram of the distribution of the test statistic. When there are more test, it produces one histogram for each test statistic.

plot: it produces the scatter plot of the (joint) distribution of the test statistics. When there are more than 2 tests, the plot is based on the first two principal components.

Usage

# S4 method for flip.object
show(object)
summary(object, ...)
# S4 method for flip.object
summary(object, star.signif = TRUE,
  only.p.leq = NULL, ...)
# S4 method for flip.object
dim(x)
# S4 method for flip.object,ANY,ANY,ANY
[(x, i)
# S4 method for flip.object
[[(x, i)
# S4 method for flip.object
length(x)
# S4 method for flip.object
names(x)
# S4 method for flip.object
names(x) <- value
# S4 method for flip.object
sort(x, decreasing = FALSE)
# S4 method for flip.object
hist(x, ...)
# S4 method for flip.object
plot(x, y, ...)

Arguments

object

a flip-object

...

additional arguments to be passed

star.signif

If TRUE (default), it puts stars on the significant tests

only.p.leq

Shows only tests with a p-value lower than only.p.leq. The default NULL is equivalent to set only.p.leq=1.

x

a flip.object.

i

indices specifying elements to extract or replace. Indices are numeric, character or logical vectors or empty (missing) or NULL.

value

character vector of up to the same length as x, or NULL.

decreasing

logical. Should the sort be increasing or decreasing?

y

not used.

Examples

Y=matrix(rnorm(50),10,5)
colnames(Y)=LETTERS[1:5]
Y[,1:2]=Y[,1:2] +2
res = flip(Y)
res
summary(res)
sort(res)
names(res)
length(res)
dim(res)
res=res[2:3]
res
hist(res)
plot(res)