1 citations · 2 across the 6 of their papers we have counts for
10 papers
Tail Halos: The Covariate Dual of the Tail
Gianmarco Callegher, Miguel de Carvalho
Extreme events are often studied through regression models describing how covariates modify tail parameters. In many applications, however, interest lies directly in identifying th…
Welcome to the Statverse: A Metaverse for Data Science
Ronny Vallejos, Miguel de Carvalho, Roberto Cruz +7
This paper introduces the Statverse, a Metaverse framework designed to revolutionize statistical education in the digital age. Our key goal is to report our progress and encourage…
A Kolmogorov-Arnold Neural Model for Cascading Extremes
Miguel de Carvalho, Clemente Ferrer, Ronny Vallejos
This paper addresses the growing concern of cascading extreme events, such as an extreme earthquake followed by a tsunami, by presenting a novel method for risk assessment focused…
The underlap coefficient as a measure of a biomarker's discriminatory ability
Zhaoxi Zhang, Vanda Inacio, Miguel de Carvalho
The first step in evaluating a potential diagnostic biomarker is to examine the variation in its values across different disease groups. In a three-class disease setting, the volum…
Using ChatGPT for Data Science Analyses
Ozan Evkaya, Miguel de Carvalho
As a result of recent advancements in generative AI, the field of data science is prone to various changes. The way practitioners construct their data science workflows is now irre…
Heavy-Tailed NGG Mixture Models
Vianey Palacios Ramirez, Miguel de Carvalho, Luis Gutierrez Inostroza
Heavy tails are often found in practice, and yet they are an Achilles heel of a variety of mainstream random probability measures such as the Dirichlet process (DP). The first cont…
Bayesian semiparametric modelling of phase-varying point processes
Bastian Galasso, Yoav Zemel, Miguel de Carvalho
We propose a Bayesian semiparametric approach for registration of multiple point processes. Our approach entails modelling the mean measures of the phase-varying point processes wi…
Affinity-based measures of medical diagnostic test accuracy
Miguel de Carvalho, Bradley J. Barney, Garritt L. Page
We propose new summary measures of diagnostic test accuracy which can be used as companions to existing diagnostic accuracy measures. Conceptually, our summary measures are tantamo…
On the geometry of Bayesian inference
Miguel de Carvalho, Garritt L. Page, Bradley J. Barney
We provide a geometric interpretation to Bayesian inference that allows us to introduce a natural measure of the level of agreement between priors, likelihoods, and posteriors. The…
A Euclidean likelihood estimator for bivariate tail dependence
Miguel de Carvalho, Boris Oumow, Johan Segers +1
The spectral measure plays a key role in the statistical modeling of multivariate extremes. Estimation of the spectral measure is a complex issue, given the need to obey a certain…