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Details

  • Name

    Maria Eduarda Silva
  • Cluster

    Computer Science
  • Role

    Research Coordinator
  • Since

    01st January 2022
Publications

2023

Time Series of Counts under Censoring: A Bayesian Approach

Authors
Silva, I; Silva, ME; Pereira, I; McCabe, B;

Publication
ENTROPY

Abstract
Censored data are frequently found in diverse fields including environmental monitoring, medicine, economics and social sciences. Censoring occurs when observations are available only for a restricted range, e.g., due to a detection limit. Ignoring censoring produces biased estimates and unreliable statistical inference. The aim of this work is to contribute to the modelling of time series of counts under censoring using convolution closed infinitely divisible (CCID) models. The emphasis is on estimation and inference problems, using Bayesian approaches with Approximate Bayesian Computation (ABC) and Gibbs sampler with Data Augmentation (GDA) algorithms.

2023

Automatic characterisation of Dansgaard-Oeschger events in palaeoclimate ice records

Authors
Barbosa, S; Silva, ME; Dias, N; Rousseau, D;

Publication

Abstract
Greenland ice core records display abrupt transitions, designated as Dansgaard-Oeschger (DO) events, characterised by episodes of rapid warming (typically decades) followed by a slower cooling. The identification of abrupt transitions is hindered by the typical low resolution and small size of paleoclimate records, and their significant temporal variability. Furthermore, the amplitude and duration of the DO events varies substantially along the last glacial period, which further hinders the objective identification of abrupt transitions from ice core records Automatic, purely data-driven methods, have the potential to foster the identification of abrupt transitions in palaeoclimate time series in an objective way, complementing the traditional identification of transitions by visual inspection of the time series.In this study we apply an algorithmic time series method, the Matrix Profile approach, to the analysis of the NGRIP Greenland ice core record, focusing on:- the ability of the method to retrieve in an automatic way abrupt transitions, by comparing the anomalies identified by the matrix profile method with the expert-based identification of DO events;- the characterisation of DO events, by classifying DO events in terms of shape and identifying events with similar warming/cooling temporal patternThe results for the NGRIP time series show that the matrix profile approach struggles to retrieve all the abrupt transitions that are identified by experts as DO events, the main limitation arising from the diversity in length of DO events and the method’s dependence on fixed-size sub-sequences within the time series. However, the matrix profile method is able to characterise the similarity of shape patterns between DO events in an objective and consistent way.

2023

MHVG2MTS: Multilayer Horizontal Visibility Graphs for Multivariate Time Series Analysis

Authors
Silva, VF; Silva, ME; Ribeiro, P; Silva, FMA;

Publication
CoRR

Abstract

2023

Multilayer Quantile Graph for Multivariate Time Series Analysis and Dimensionality Reduction

Authors
Silva, VF; Silva, ME; Ribeiro, P; Silva, FMA;

Publication
CoRR

Abstract

2022

Empirical Evidence of Associations and Similarities between the National Equity Markets Indexes and Crude Oil Prices in the International Market

Authors
Salles, AAd; Silva, ME; Teles, P;

Publication
Open Journal of Business and Management

Abstract

Supervised
thesis

2022

Effectiveness and Accessibility of Graphical Representations for depicting the COVID-19 Pandemic Hazard

Author
Maria Teresa Miranda Teixeira da Mota

Institution
UP-FEP

2022

Public Online Activity Data Sources and Unemployment Prediction.

Author
Eduardo André Moura Martins Costa

Institution
UP-FEP

2022

Data visualization for the Internal Audit function at MC

Author
Marta Sofia Guerra Conceição Teixeira de Moraes

Institution
UP-FEP

2022

Time Series Forecasting via Network Science

Author
Filipe Godinho Justiça

Institution
UP-FCUP

2022

Short-Term Forecasting of MIBEL Day-Ahead Prices

Author
Paulo Coelho Moreira de Azevedo

Institution
UP-FEP