7 citations · 17 across the 10 of their papers we have counts for
12 papers
Modelling non-stationary extremal dependence through a geometric approach
C. J. R. Murphy-Barltrop, J. L. Wadsworth, M. de Carvalho +1
Non-stationary extremal dependence, whereby the relationship between the extremes of multiple variables evolves over time, is commonly observed in many environmental and financial…
A parallelizable model-based approach for marginal and multivariate clustering
Miguel de Carvalho, Gabriel Martos Venturini, Andrej Svetlošák
This paper develops a clustering method that takes advantage of the sturdiness of model-based clustering, while attempting to mitigate some of its pitfalls. First, we note that sta…
Uncovering Regions of Maximum Dissimilarity on Random Process Data
Miguel de Carvalho, Gabriel Martos Venturini
The comparison of local characteristics of two random processes can shed light on periods of time or space at which the processes differ the most. This paper proposes a method that…
Regression-type analysis for block maxima on block maxima
Miguel de Carvalho, Gonçalo dos Reis, Alina Kumukova
This paper devises a regression-type model for the situation where both the response and covariates are extreme. The proposed approach is designed for the setting where both the re…
Tracking change-points in multivariate extremes
Miguel de Carvalho, Manuele Leonelli, Alex Rossi
In this paper we devise a statistical method for tracking and modeling change-points on the dependence structure of multivariate extremes. The methods are motivated by and illustra…
Modeling Interval Trendlines: Symbolic Singular Spectrum Analysis for Interval Time Series
Miguel de Carvalho, Gabriel Martos
In this article we propose an extension of singular spectrum analysis for interval-valued time series. The proposed methods can be used to decompose and forecast the dynamics gover…
An Extreme Value Bayesian Lasso for the Conditional Left and Right Tails
Miguel de Carvalho, Soraia Pereira, Paula Pereira +1
We introduce a novel regression model for the conditional left and right tail of a possibly heavy-tailed response. The proposed model can be used to learn the effect of covariates…
Calibration methods for spatial Data
M A Amaral Turkman, K F Turkman, P de Zea Bermudez +3
In an environmental framework, extreme values of certain spatio-temporal processes, for example wind speeds, are the main cause of severe damage in property, such as electrical net…
Robust and flexible inference for the covariate-specific ROC curve
Vanda Inacio, Vanda M. Lourenco, Miguel de Carvalho +2
Diagnostic tests are of critical importance in health care and medical research. Motivated by the impact that atypical and outlying test outcomes might have on the assessment of th…
Bayesian Bootstrap Inference for the ROC Surface
Vanda Inacio de Carvalho, Miguel de Carvalho, Adam Branscum
Accurate diagnosis of disease is of great importance in clinical practice and medical research. The receiver operating characteristic (ROC) surface is a popular tool for evaluating…
Time-Varying Extreme Value Dependence with Application to Leading European Stock Markets
Daniela Castro Camilo, Miguel de Carvalho, Jennifer Wadsworth
Extremal dependence between international stock markets is of particular interest in today's global financial landscape. However, previous studies have shown this dependence is not…
Regression Type Models for Extremal Dependence
Linda Mhalla, Miguel de Carvalho, Valérie Chavez-Demoulin
We propose a vector generalized additive modeling framework for taking into account the effect of covariates on angular density functions in a multivariate extreme value context. T…