Description Usage Arguments Details Value Author(s) References See Also Examples
Test whether or not there is association betwenn two data sets, with a focus on robust and nonparametric correlation measures.
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x, y 
each can be a numeric vector, matrix or data frame. 
R 
an integer giving the number of random permutations to be used. 
fun 
a function to compute a maximum correlation measure between
two data sets, e.g., 
permutations 
an integer matrix in which each column contains the
indices of a permutation. If supplied, this is preferred over 
nCores 
a positive integer giving the number of processor cores to be
used for parallel computing (the default is 1 for no parallelization). If
this is set to 
cl 
a parallel cluster for parallel computing as generated by

seed 
optional integer giving the initial seed for the random number
generator (see 
... 
additional arguments to be passed to 
The test generates R
data sets by randomly permuting the observations
of x
, while keeping the observations of y
fixed. In each
replication, a function to compute a maximum correlation measure is
applied to the permuted data sets. The pvalue of the test is then
given by the percentage of replicates of the maximum correlation measure
that are larger than the maximum correlation measure computed from the
original data.
An object of class "permTest"
with the following components:
pValue 
the pvalue for the test. 
cor0 
the value of the test statistic. 
cor 
the values of the test statistic for each of the permutated data sets. 
R 
the number of random permutations. 
seed 
the seed of the random number generator. 
call 
the matched function call. 
Andreas Alfons
A. Alfons, C. Croux and P. Filzmoser (2016) Robust maximum association between data sets: The R Package ccaPP. Austrian Journal of Statistics, 45(1), 71–79.
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