Observed Range Maximum Likelihood Estimation
Abstract
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.
Cite
@article{arxiv.1111.4196,
title = {Observed Range Maximum Likelihood Estimation},
author = {Plamen Markov},
journal= {arXiv preprint arXiv:1111.4196},
year = {2011}
}
Comments
censored multivariate data, contingency tables with incomplete counts, nonparametric density estimation, nonparametric regression