2012/03/17 by Chanseok Park, Park, Chanseok, Seong Beom Lee +1
Mathematics · Decision Sciences · #Statistical Distribution Estimation and Applications #Statistical Methods and Inference #Probabilistic and Robust Engineering Design
paper · pdf · doi:10.48550/arxiv.1203.3880
This paper deals with parameter estimation when the data are randomly right censored. The maximum likelihood estimates from censored samples are obtained by using the expectation-maximization (EM) and Monte Carlo EM (MCEM) algorithms. We introduce the concept of the EM and MCEM algorithms and develop parameter estimation methods for a variety of distributions such as normal, Laplace and Rayleigh distributions. These proposed methods are illustrated with three examples.