activity
20142023
most citedAssessing phenotypic correlation through the multivariate phylogenetic latent liability model

40 citations · 41 across the 6 of their papers we have counts for

collaborators

6 papers

stat.ME2023

Bayesian Analysis of Beta Autoregressive Moving Average Models

Aline Foerster Grande, Guilherme Pumi, Gabriela Bettella Cybis

This work presents a Bayesian approach for the estimation of Beta Autoregressive Moving Average (ARMA) models. We discuss standard choice for the prior distributions and employ…

stat.ME2022

Sparse precision matrix estimation in phenotypic trait evolution models

Felipe G. Pinheiro, Taiane S. Prass, Gabriel W. Hassler +2

Phylogenetic trait evolution models allow for the estimation of evolutionary correlations between a set of traits observed in a sample of related organisms. By directly modeling th…

stat.ME2021

Clustering inference in multiple groups

Debora Zava Bello, Marcio Valk, Gabriela Bettella Cybis

Inference in clustering is paramount to uncovering inherent group structure in data. Clustering methods which assess statistical significance have recently drawn attention owing to…

stat.ME2018★ 1 cited

U-statistical inference for hierarchical clustering

Marcio Valk, Gabriela Bettella Cybis

Clustering methods are a valuable tool for the identification of patterns in high dimensional data with applications in many scientific problems. However, quantifying uncertainty i…

stat.ME2016

Clustering and Classification of Genetic Data Through U-Statistics

Gabriela Bettella Cybis, Marcio Valk, Silvia Regina Costa Lopes

Genetic data are frequently categorical and have complex dependence structures that are not always well understood. For this reason, clustering and classification based on genetic…

q-bio.PE2014★ 40 cited

Assessing phenotypic correlation through the multivariate phylogenetic latent liability model

Gabriela B. Cybis, Janet S. Sinsheimer, Trevor Bedford +3

Understanding which phenotypic traits are consistently correlated throughout evolution is a highly pertinent problem in modern evolutionary biology. Here, we propose a multivariate…