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20232026
most citedA minimum Wasserstein distance approach to Fisher's combination of independent discrete p-values

1 citations · 1 across the 6 of their papers we have counts for

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6 papers

math.OC2026

Sharp bounds for stochastic proximal and projection estimators via radial dominance

Gonzalo Contador, Pedro Pérez-Aros, Emilio Vilches

We study stochastic barycentric estimators for proximal points and metric projections obtained by exponentially reweighting Gaussian perturbations. Our main result is an abstract c…

stat.ME2025

Optimal Adjustment and Combination of Independent Discrete -Values

Gonzalo Contador, Zheyang Wu

Combining p-values from multiple independent tests is a fundamental task in statistical inference, but presents unique challenges when the p-values are discrete. We extend a recent…

math.OC2024

Differentiability and Approximation of Probability Functions under Gaussian Mixture Models

Gonzalo Contador, Pedro Pérez-Aros, Emilio Vilches

In this work, we study probability functions associated with Gaussian mixture models. Our primary focus is on extending the use of spherical radial decomposition for multivariate G…

stat.AP2024

Another reason why normalized gain should continue to be used to analyze concept inventories (and estimate learning rates)

Jairo Navarrete, Valentina Giaconi, Gonzalo Contador +1

A transformation called normalized gain (ngain) has been acknowledged as one of the most common measures of knowledge growth in pretest-posttest contexts in physics education resea…

math.ST2023★ 1 cited

A minimum Wasserstein distance approach to Fisher's combination of independent discrete p-values

Gonzalo Contador, Zheyang Wu

This paper introduces a comprehensive framework to adjust a discrete test statistic for improving its hypothesis testing procedure. The adjustment minimizes the Wasserstein distanc…

math.ST2023

Sampling distributions and estimation for multi-type Branching Processes

Gonzalo Contador, Bret Hanlon

Consider a multi-dimensional supercritical branching process with offspring distribution in a parametric family. Here, each vector coordinate corresponds to the number of offspring…