publications

2026

1. 

   Inferring tephritid fly pupal development stage using non-invasive near infrared imaging and machine learning classification

   Guadalupe Córdova-García, Horacio Tapia-McClung, Dinesh Rao, and 1 more author

   Bulletin of Entomological Research, 2026

   DOI

2025

1. 

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

   Héctor Francisco Coronel-Brizio, Alejandro Raúl Hernández-Montoya, Manuel Enrique Rodríguez-Achach, and 2 more authors

   PLOS ONE, Dec 2025

   Abs DOI

   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.

2. 

   On the Autocorrelation and Stationarity of Multi-Scale Returns

   Carlos Manuel Rodríguez-Martínez, Héctor Francisco Coronel-Brizio, Horacio Tapia-McClung, and 2 more authors

   Mathematics, 2025

   Abs DOI

   In this article, we conduct a statistical analysis of the autocorrelation functions (ACF) of multi-scale logarithmic returns computed over maximal monotonic uninterrupted trends (runs) in financial indices’ daily data. We analyze the Dow Jones Industrial Average (DJIA) and the Mexican IPC (Índice de Precios y Cotizaciones) over a period from 30 October 1978 to 19 May 2025. We examine how deterministic alternation of signs shapes the ACF of multi-scale returns, and we evaluate covariance stationarity via formal tests (e.g., Augmented Dickey–Fuller and Phillips–Perron). We conclude that, despite the persistent long-memory oscillations in the ACF, multi-scale return series pass the stationarity tests, an outcome with interesting implications for econometric modeling of financial time series.