Maximum-Likelihood Estimation of a Log-Concave Density based on Censored Data
Methodology
2014-08-15 v3 Computation
Abstract
We consider nonparametric maximum-likelihood estimation of a log-concave density in case of interval-censored, right-censored and binned data. We allow for the possibility of a subprobability density with an additional mass at , which is estimated simultaneously. The existence of the estimator is proved under mild conditions and various theoretical aspects are given, such as certain shape and consistency properties. An EM algorithm is proposed for the approximate computation of the estimator and its performance is illustrated in two examples.
Cite
@article{arxiv.1311.6403,
title = {Maximum-Likelihood Estimation of a Log-Concave Density based on Censored Data},
author = {Lutz Duembgen and Kaspar Rufibach and Dominic Schuhmacher},
journal= {arXiv preprint arXiv:1311.6403},
year = {2014}
}