  Variations of the commonly applied landmark sampling are presented. These
samplings are "forward" landmarking such that each stack of data is created by
first selecting landmarks and then including the subsequent observations of the
selected landmarks. Unlike these forward landmarking samplings, a "backward" or
"reverse" landmarking is proposed with a flexible "progressive" weighting on
selecting different types of events and non-events. The backward landmark
sample is compared with those forward landmark samples with a real world
mortgage data. Results show that the backward landmark sample has smaller
sampling errors than of those forward landmark samples.
