  The idea of maximizing the likelihood of the observed range for a set of
jointly realized counts has been employed in a variety of contexts. The
applicability of the MLE introduced in [1] has been extended to the general
case of a multivariate sample containing interval censored outcomes. In
addition, a kernel density estimator and a related score function have been
proposed leading to the construction of a modified Nadaraya-Watson regression
estimator. Finally, the author has treated the problems of estimating the
parameters of a mutinomial distribution and the analysis of contingency tables
in the presence of censoring.
