A carregar...
Projeto de investigação
Sem título
Financiador
Autores
Publicações
A spatial econometric analysis of the calls to the portuguese national health line
Publication . Simões, Paula; Carvalho, M. Lucília; Aleixo, Sandra; Gomes, Sérgio; Natário, Isabel; CMA - Centro de Matemática e Aplicações; DM - Departamento de Matemática; MDPI - Multidisciplinary Digital Publishing Institute
The Portuguese National Health Line, LS24, is an initiative of the Portuguese Health Ministry which seeks to improve accessibility to health care and to rationalize the use of existing resources by directing users to the most appropriate institutions of the national public health services. This study aims to describe and evaluate the use of LS24. Since for LS24 data, the location attribute is an important source of information to describe its use, this study analyses the number of calls received, at a municipal level, under two different spatial econometric approaches. This analysis is important for future development of decision support indicators in a hospital context, based on the economic impact of the use of this health line. Considering the discrete nature of data, the number of calls to LS24 in each municipality is better modelled by a Poisson model, with some possible covariates: demographic, socio-economic information, characteristics of the Portuguese health system and development indicators. In order to explain model spatial variability, the data autocorrelation can be explained in a Bayesian setting through different hierarchical log-Poisson regression models. A different approach uses an autoregressive methodology, also for count data. A log-Poisson model with a spatial lag autocorrelation component is further considered, better framed under a Bayesian paradigm. With this empirical study we find strong evidence for a spatial structure in the data and obtain similar conclusions with both perspectives of the analysis. This supports the view that the addition of a spatial structure to the model improves estimation, even in the case where some relevant covariates have been included.
Testing conditions and estimating parameters in extreme value theory: Application to environmental data
Publication . Penalva, Helena; Gomes, Dora Prata; Neves, M. Manuela; Nunes, Sandra; CMA - Centro de Matemática e Aplicações; INE - Instituto Nacional de Estatística
Extreme Value Theory has been asserting itself as one of the most important statistical theories for the applied sciences providing a solid theoretical basis for deriving statistical models describing extreme or even rare events. The efficiency of the inference and estimation procedures depends on the tail shape of the distribution underlying the data. In this work we will present a review of tests for assessing extreme value conditions and for the choice of the extreme value domain. Motivated by two real environmental problems we will apply those tests showing the need of performing such tests for choosing the most appropriate parameter estimation methods.
Unidades organizacionais
Descrição
Palavras-chave
Contribuidores
Financiadores
Entidade financiadora
Fundação para a Ciência e a Tecnologia
Programa de financiamento
5876
Número da atribuição
UID/MAT/00006/2013