Browsing by Author "Duczmal, Denise Bulgarelli"

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    Nonparametric dependence modeling via cluster analysis : a financial contagion application.
    (2019) Couto, Ricardo; Duczmal, Luiz Henrique; Duczmal, Denise Bulgarelli; Álvares, Felipe; Moreira, Gladston Juliano Prates
    Dependence measures, from linear correlation coefficients to recent copula-based methods, have been widely used to find out associations between variables. Although the latter type of measure has overcome many drawbacks of traditional measures, copula has intrinsically some undesirable characteristics for particular applications. In this paper, we discuss dependence modeling from a pattern recognition perspective and then introduce a new non-parametric approach based on anomaly detection through cluster analysis. The proposed methodology uses a weighting procedure based on Voronoi cells densities, named Weighted Voronoi Distance (WVD), to identify potentially atypical associations between univariate time series. The advantages are two-fold. First, the time series structure is respected and neither independence nor homoscedasticity is presumed within data. Second, any distribution of the data and any dependence function is allowed. An inference procedure is presented and simulation studies help to visualize the behavior and benefits of the proposed measure. Finally, real financial data is used to analyze the detection capacity of the contagion effect in financial markets during the 2007 sub-prime crisis. Different asset classes were included, and the WVD was able to signalize anomalies more strongly than the Extreme Value Theory and copula approach.
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    Vertical social distancing policy is ineffective to contain the COVID-19 pandemic.
    (2020) Duczmal, Luiz Henrique; Almeida, Alexandre Celestino Leite de; Duczmal, Denise Bulgarelli; Alves, Claudia Regina Lindgren; Magalhães, Flávia Costa Oliveira; Lima, Max Sousa de; Silva, Ivair Ramos; Takahashi, Ricardo Hiroshi Caldeira
    Considering numerical simulations, this study shows that the so-called vertical social distancing health policy is ineffective to contain the COVID-19 pandemic. We present the SEIR-Net model, for a network of social group interactions, as a development of the classic mathematical model of SEIR epidemics (Susceptible-Exposed-Infected (symptomatic and asymptomatic)- Removed). In the SEIR-Net model, we can simulate social contacts between groups divided by age groups and analyze different strategies of social distancing. In the vertical distancing policy, only older people are distanced, whereas in the horizontal distancing policy all age groups adhere to social distancing. These two scenarios are compared to a control scenario in which no intervention is made to distance people. The vertical distancing scenario is almost as bad as the control, both in terms of people infected and in the acceleration of cases. On the other hand, horizontal distancing, if applied with the same intensity in all age groups, significantly reduces the total infected people “flattening the disease growth curve”. Our analysis considers the city of Belo Horizonte, Minas Gerais State, Brazil, but similar conclusions apply to other cities as well. Code implementation of the model in R-language is provided in the supplementary material.
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    Voronoi distance based prospective space-time scans for point data sets : a dengue fever cluster analysis in a southeast Brazilian town.
    (2011) Duczmal, Luiz Henrique; Moreira, Gladston Juliano Prates; Duczmal, Denise Bulgarelli; Takahashi, Ricardo Hiroshi Caldeira; Magalhães, Flávia Costa Oliveira; Bodevan, Emerson Cotta
    The Prospective Space-Time scan statistic (PST) is widely used for the evaluation of space-time clusters of point event data. Usually a window of cylindrical shape is employed, with a circular or elliptical base in the space domain. Recently, the concept of Minimum Spanning Tree (MST) was applied to specify the set of potential clusters, through the Density-Equalizing Euclidean MST (DEEMST) method, for the detection of arbitrarily shaped clusters. The original map is cartogram transformed, such that the control points are spread uniformly. That method is quite effective, but the cartogram construction is computationally expensive and complicated.