  Ordered random vectors are frequently encountered in many problems. The
generalized order statistics (GOS) and sequential order statistics (SOS) are
two general models for ordered random vectors. However, these two models do not
capture the dependency structures that are present in the underlying random
variables. In this paper, we study the developed sequential order statistics
(DSOS) and developed generalized order statistics (DGOS) models that describe
the dependency structures of ordered random vectors. We then study various
univariate and multivariate ordering properties of DSOS and DGOS models under
Archimedean copula. We consider both one-sample and two-sample scenarios and
develop corresponding results.
