@article{Mosilhy2023, 
author = {Mohamed Ahmed Mosilhy},
title = {Discrete Erlang-2 distribution and its application to leukemia and COVID-19},
year = {2023},
journal = {AIMS Mathematics},
volume = {8},
number = {5},
pages = {10266-10282},
keywords = {leukemia and COVID-19 data, discretization, reliability analysis, Erlang-2 distribution, maximum likelihood estimator, Fano factor},
url = {https://www.sciopen.com/article/10.3934/math.2023520},
doi = {10.3934/math.2023520},
abstract = {Via the survival discretization method, this research revealed a novel discrete one-parameter distribution known as the discrete Erlang-2 distribution (DE2). The new distribution has numerous surprising improvements over many conventional discrete distributions, particularly when analyzing excessively dispersed count data. Moments and moments-generating functions, a few descriptive measures (central tendency and dispersion), monotonicity of the probability mass function, and the hazard rate function are just a few of the statistical aspects of the postulated distribution that have been developed. The single parameter of the DE2 distribution was estimated via the maximum likelihood technique. Real-world datasets, leukemia and COVID-19, were applied to analyze the effectiveness of the recommended distribution.}
}