Robust Estimators and Test-Statistics for One-Shot Device Testing Under the Exponential Distribution
Methodology
2017-04-27 v1
Abstract
This paper develops a new family of estimators, the minimum density power divergence estimators (MDPDEs), for the parameters of the one-shot device model as well as a new family of test statistics, Z-type test statistics based on MDPDEs, for testing the corresponding model parameters. The family of MDPDEs contains as a particular case the maximum likelihood estimator (MLE) considered in Balakrishnan and Ling (2012). Through a simulation study, it is shown that some MDPDEs have a better behavior than the MLE in relation to robustness. At the same time, it can be seen that some Z-type tests based on MDPDEs have a better behavior than the classical Z-test statistic also in terms of robustness.
Cite
@article{arxiv.1704.07865,
title = {Robust Estimators and Test-Statistics for One-Shot Device Testing Under the Exponential Distribution},
author = {N. Balakrishnan and E. Castilla and N. Martin and L. Pardo},
journal= {arXiv preprint arXiv:1704.07865},
year = {2017}
}