3 citations · 4 across the 5 of their papers we have counts for
5 papers
Statistics of Extremes for Neuroscience
Paolo V. Redondo, Matheus B. Guerrero, Raphaël Huser +1
This chapter illustrates how tools from univariate and multivariate statistics of extremes can complement classical methods used to study brain signals and enhance the understandin…
Modern extreme value statistics for Utopian extremes
Jordan Richards, Noura Alotaibi, Daniela Cisneros +4
Capturing the extremal behaviour of data often requires bespoke marginal and dependence models which are grounded in rigorous asymptotic theory, and hence provide reliable extrapol…
Club Exco: clustering brain extreme communities from multi-channel EEG data
Matheus B. Guerrero, Paolo V. Redondo, Marco A. Pinto-Orellana +3
Current methods for clustering brain networks over time often rely on cross-dependence measures computed from the entire range of EEG signals, which can obscure information specifi…
Conex-Connect: Learning Patterns in Extremal Brain Connectivity From Multi-Channel EEG Data
Matheus B. Guerrero, Raphaël Huser, Hernando Ombao
Epilepsy is a chronic neurological disorder affecting more than 50 million people globally. An epileptic seizure acts like a temporary shock to the neuronal system, disrupting norm…
Integer-valued autoregressive process with flexible marginal and innovation distributions
Matheus B. Guerrero, Wagner Barreto-Souza, Hernando Ombao
INteger Auto-Regressive (INAR) processes are usually defined by specifying the innovations and the operator, which often leads to difficulties in deriving marginal properties of th…