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Detalhes

Detalhes

  • Nome

    Sónia Dias
  • Cluster

    Informática
  • Cargo

    Investigador Sénior
  • Desde

    01 abril 2012
Publicações

2018

Agent-based model of diffusion of N-acyl homoserine lactones in a multicellular environment of Pseudomonas aeruginosa and Candida albicans

Autores
Pérez-Rodríguez, G; Dias, S; Pérez-Pérez, M; Fdez-Riverola, F; Azevedo, NF; Lourenço, A;

Publicação
Biofouling

Abstract

2017

Off the beaten track: A new linear model for interval data

Autores
Dias, S; Brito, P;

Publicação
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
We propose a new linear regression model for interval-valued variables. The model uses quantile functions to represent the intervals, thereby considering the distributions within them. In this paper we study the special case where the Uniform distribution is assumed in each observed interval, and we analyze the extension to the Symmetric Triangular distribution. The parameters of the model are obtained solving a constrained quadratic optimization problem that uses the Mallows distance between quantile functions. As in the classical case, a goodness-of-fit measure is deduced. Two applications on up-to-date fields are presented: one predicting duration of unemployment and the other allowing forecasting burned area by forest fires.

2015

Linear regression model with histogram-valued variables

Autores
Dias, S; Brito, P;

Publicação
Statistical Analysis and Data Mining

Abstract
Histogram-valued variables are a particular kind of variables studied in Symbolic Data Analysis where to each entity under analysis corresponds a distribution that may be represented by a histogram or by a quantile function. Linear regression models for this type of data are necessarily more complex than a simple generalization of the classical model: the parameters cannot be negative; still the linear relation between the variables must be allowed to be either direct or inverse. In this work, we propose a new linear regression model for histogram-valued variables that solves this problem, named Distribution and Symmetric Distribution Regression Model. To determine the parameters of this model, it is necessary to solve a quadratic optimization problem, subject to non-negativity constraints on the unknowns; the error measure between the predicted and observed distributions uses the Mallows distance. As in classical analysis, the model is associated with a goodness-of-fit measure whose values range between 0 and 1. Using the proposed model, applications with real and simulated data are presented. © 2015 Wiley Periodicals, Inc.

2012

Linear regression models in data frameworks with variability.

Autores
Sónia Dias; Paula Brito

Publicação
COMPSTAT 2011 - International Conference on Computational Statistics, Limassol, Chipre

Abstract

2012

New developments in linear regression models with histogram-valued variables

Autores
Sónia Dias; Paula Brito

Publicação
SDA2012 - Workshop in Symbolic Data Analysis, Madrid, Espanha

Abstract

Teses
supervisionadas

2017

Modelos de Regressão Linear para Variáveis Intervalares: Uma extensão do modelo ID

Autor
Pedro Jorge Correia Malaquias

Instituição
UP-FEP