pairwiseCcop() array
which contains pairwise Rosenblatt-transformed data.
pairwiseIndepTest() matrix of test results from
pairwise tests of independence (as by indepTest()).
pviTest() pairwiseIndepTest().
gpviTest()
pairwiseCcop(u, cop, ...)
pairwiseIndepTest(cu.u, N=256, iTest = indepTestSim(n, p=2, m=2, N=N, verbose = idT.verbose, ...), verbose=TRUE, idT.verbose = verbose, ...)
pviTest(piTest)
gpviTest(pvalues, method=p.adjust.methods, globalFun=min)matrix of copula data.pairwiseCcop()).
Can be used to pass, for example, the degrees of freedom
parameter df for t-copulas. For pairwiseIndepTest(),
... are passed to indepTestSim().
array as returned by
pairwiseCcop().indepTestSim().indepTestSim();
as it does not depend on the data, and is costly to compute,
it can be computed separately and passed here.verbose argument to
indepTestSim().matrix of indepTest
objects as returned by pairwiseIndepTest().matrix of p-values.character vector of adjustment methods for
p-values; see p.adjust.methods for more details.function determining how to compute a
global p-value from a matrix of pairwise adjusted p-values.array cu.u
with cu.u[i,j] containing $C(u[,i]|u[,j])$
for $i!=j$ and $u[,i]$ for $i=j$.matrix of lists
with test results as returned by indepTest(). The
test results correspond to pairwise tests of independence as
conducted by indepTest().matrix of p-values.pairsRosenblatt.
pairsRosenblatt
for where these tools are used, including
demo(gof_graph) for examples.