  Any nested Archimedean copula is defined starting from a rooted phylogenetic
tree, for which a new class of nonparametric estimators is presented. An
estimator from this new class relies on a two-step procedure where first a
binary tree is built and second is collapsed if necessary to give an estimate
of the target tree structure. Several examples of estimators from this class
are given and the performance of each of these estimators, as well as of the
only known comparable estimator, is assessed by means of a simulation study
involving target structures in various dimensions, showing that the new
estimators, besides being faster, usually offer better performance as well.
Further, among the given examples of estimators from the new class, one of the
best performing one is applied on three datasets: 482 students and their
results to various examens, 26 European countries in 1979 and the percentage of
workers employed in different economic activities, and 104 countries in 2002
for which various health-related variables are available. The resulting
estimated trees offer valuable insights on the analyzed data. The future of
nested Archimedean copulas in general is also discussed.
