Anderson-Darling and Watson tests for the geometric distribution with estimated probability of success.

Autor:	Coronel-Brizio HF; Instituto de Investigaciones en Inteligencia Artificial, Universidad Veracruzana, Xalapa, Veracruz, México.; Facultad de Física, Universidad Veracruzana, Xalapa, Veracruz, México., Hernández-Montoya AR; Instituto de Investigaciones en Inteligencia Artificial, Universidad Veracruzana, Xalapa, Veracruz, México.; Facultad de Física, Universidad Veracruzana, Xalapa, Veracruz, México., Rodríguez-Achach ME; Unidad Experimental Marista (UNEXMAR), Universidad Marista de Mérida, Mérida, Yucatán, México., Tapia-McClung H; Instituto de Investigaciones en Inteligencia Artificial, Universidad Veracruzana, Xalapa, Veracruz, México., Trinidad-Segovia JE; Departamento de Economía y Empresa, Universidad de Almería (UAL), Almería, España.
Jazyk:	angličtina
Zdroj:	PloS one [PLoS One] 2024 Dec 31; Vol. 19 (12), pp. e0315855. Date of Electronic Publication: 2024 Dec 31 (Print Publication: 2024).
DOI:	10.1371/journal.pone.0315855
Abstrakt:	This paper introduces two new goodness-of-fit tests for the geometric distribution based on discrete adaptations of the Watson W2 and Anderson-Darling A2 statistics, where the probability of success is unknown. Although these tests are widely applied to continuous distributions, their application in discrete models has been relatively unexplored. Our study addresses this need by developing a robust statistical framework specifically for discrete distributions, particularly the geometric distribution. We provide extensive tables of asymptotic critical values for these tests and demonstrate their practical relevance through a financial case study. Specifically, we apply these tests to analyze price runs derived from daily time series of NASDAQ, DJIA, Nikkei 225, and the Mexican IPC indices, covering the period from January 1, 2015, to December 31, 2022. This work broadens the range of available tools for assessing goodness-of-fit in discrete models, which are essential for applications in finance and beyond. The Python programs developed for this paper are available to the academic community. Competing Interests: The authors have declared that no competing interests exist. (Copyright: © 2024 Coronel-Brizio et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze:	MEDLINE
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