TY - JOUR
T1 - Goodness of fit for the Waring distribution
AU - Tang, Yanlin
AU - Wang, Jinglong
AU - Yi, Menghan
AU - Zhu, Zhongyi
N1 - Publisher Copyright:
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2025
Y1 - 2025
N2 - The Waring distribution is an important two-parameter discrete distribution, commonly used in fields such as ecology, linguistics, and information science, where heavy tails are often observed. In this paper, we propose a new goodness-of-fit test for the Waring distribution, which is established through the hazard rate and a linear equivalent definition of the Waring distribution. We establish an asymptotic Chi-square null distribution for the proposed test and show that it is more powerful than classical methods in simulation studies. Finally, we apply the test to analyze the authorships of published papers on computer science.
AB - The Waring distribution is an important two-parameter discrete distribution, commonly used in fields such as ecology, linguistics, and information science, where heavy tails are often observed. In this paper, we propose a new goodness-of-fit test for the Waring distribution, which is established through the hazard rate and a linear equivalent definition of the Waring distribution. We establish an asymptotic Chi-square null distribution for the proposed test and show that it is more powerful than classical methods in simulation studies. Finally, we apply the test to analyze the authorships of published papers on computer science.
KW - Waring distribution
KW - goodness-of-fit test
KW - hazard rate
KW - long-tailed distribution
UR - https://www.scopus.com/pages/publications/105001498753
U2 - 10.1080/24754269.2024.2389758
DO - 10.1080/24754269.2024.2389758
M3 - 文章
AN - SCOPUS:105001498753
SN - 2475-4269
VL - 9
SP - 1
EP - 11
JO - Statistical Theory and Related Fields
JF - Statistical Theory and Related Fields
IS - 1
ER -