Fixed-point algorithms for solving the critical value and upper tail quantile of Kuiper's statistics

Autor: Hong-Yan Zhang, Wei Sun, Xiao Chen, Rui-Jia Lin, Yu Zhou
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Heliyon, Vol 10, Iss 7, Pp e28274- (2024)
Druh dokumentu: article
ISSN: 2405-8440
DOI: 10.1016/j.heliyon.2024.e28274
Popis: Kuiper's statistic is a good measure for the difference of ideal distribution and empirical distribution in the goodness-of-fit test. However, it is a challenging problem to solve the critical value and upper tail quantile, or simply Kuiper pair, of Kuiper's statistics due to the difficulties of solving the nonlinear equation and reasonable approximation of infinite series. In this work, the contributions lie in three perspectives: firstly, the second order approximation for the infinite series of the cumulative distribution of the critical value is used to achieve higher precision; secondly, the principles and fixed-point algorithms for solving the Kuiper pair are presented with details; finally, finally, a mistake about the critical value cnα for (α,n)=(0.01,30) in Kuiper's distribution table has been labeled and corrected where n is the sample capacity and α is the upper tail quantile. The algorithms are verified and validated by comparing with the table provided by Kuiper. The methods and algorithms proposed are enlightening and worth of introducing to the college students, computer programmers, engineers, experimental psychologists and so on.
Databáze: Directory of Open Access Journals