activity
20182026
collaborators

6 papers

q-bio.PE2026

Novel models of trait evolution via an expansion of Lande's fitness function: The Ornstein-Uhlenbeck process meets the Little Prince's boa

Jose M Ponciano, Claire Godineau, Laura Jimenez +3

Adaptive topographies form the foundation for much of our understanding of evolutionary change. Lande's 1976 influential paper on the adaptive topography of phenotypes demonstrated…

stat.ME2024

Evidential Analysis: An Alternative to Hypothesis Testing in Normal Linear Models

Brian Dennis, Mark L Taper, José M Ponciano

Statistical hypothesis testing, as formalized by 20th Century statisticians and taught in college statistics courses, has been a cornerstone of 100 years of scientific progress. Ne…

q-bio.PE2022

COVID-19 Regional Waves and Spread Risk Assessment through the Analysis of the Initial Outbreak in Guatemala

Juan Adolfo Ponciano, Juan Diego Chang, Mariela Abdalah +2

The initial surge of the COVID-19 pandemic hit Guatemala on March 2020. On a country scale, the epidemic has undergone a fairly well-known and distinguishable initial phase, reachi…

q-bio.PE2020

Poverty levels, societal and individual heterogeneities explain the SARS-CoV-2 pandemic growth in Latin America

José Miguel Ponciano, Juan Adolfo Ponciano, Juan Pablo Gómez +2

Latin America is experiencing severe impacts of the SARS-CoV-2 pandemic, but poverty and weak public health institutions hamper gathering the kind of refined data needed to inform…

stat.ME2019

Assessing the global and local uncertainty in scientific evidence in the presence of model misspecification

Mark L. Taper, Subhash R Lele, José-Miguel Ponciano +2

Scientists need to compare the support for models based on observed phenomena. The main goal of the evidential paradigm is to quantify the strength of evidence in the data for a re…

stat.ME2018

Multi-model inference through projections in model space

Jose-Miguel Ponciano, Mark L Taper

Information criteria have had a profound impact on modern ecological science. They allow researchers to estimate which probabilistic approximating models are closest to the generat…