A new simple and powerful normality test for progressively Type-II censored data
Statistics Theory
2017-04-25 v1 Statistics Theory
Abstract
In this paper, a new goodness-of-fit test for a location-scale family based on progressively Type-II censored order statistics is proposed. Using Monte Carlo simulation studies, the present researchers have observed that the proposed test for normality is consistent and quite powerful in comparison with existing goodness-of-fit tests based on progressively Type-II censored data. Also, the new test statistic for a real data set is used and the results show that our new test statistic performs well.
Cite
@article{arxiv.1704.06787,
title = {A new simple and powerful normality test for progressively Type-II censored data},
author = {Hamzeh Torabi and Sayyed Mahmoud Mirjalili and Hossein Nadeb},
journal= {arXiv preprint arXiv:1704.06787},
year = {2017}
}