The book concerns the notion of association in probability and
statistics. Association and some other positive dependence notions
were introduced in 1966 and 1967 but received little attention from
the probabilistic and statistics community. The interest in these
dependence notions increased in the last 15 to 20 years, and many
asymptotic results were proved and improved. Despite this increased
interest, characterizations and results remained essentially
scattered in the literature published in different journals. The
goal of this book is to bring together the bulk of these results,
presenting the theory in a unified way, explaining relations and
implications of the results. It will present basic definitions and
characterizations, followed by a collection of relevant
inequalities. These are then applied to characterize almost sure
and weak convergence of sequences of associated variables. It will
also cover applications of positive dependence to the
characterization of asymptotic results in nonparametric statistics.
The book is directed towards researchers in probability and
statistics, with particular emphasis on people interested in
nonparametric methods. It will also be of interest to graduate
students in those areas. The book could also be used as a reference
on association in a course covering dependent variables and their
asymptotics.
As prerequisite, readers should have knowledge of basic probability
on the reals and on metric spaces. Some acquaintance with the
asymptotics of random functions, such us empirical processes and
partial sums processes, is useful but not essential.
General
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