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Assessing the performance of change-point detection based on the SIC procedure for non Gaussian and correlated data - a simulation study

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Detalhes bibliográficos
Resumo:A simulation study is conducted in order to assess the impact of autocorrelation and non-normality on change-point detection when it is performed by the Schwarz Information Criterion (SIC) approach. Change-point detection in environmental data is usually fulfilled in the presence of time correlation or non-Gaussian distribution. This work analyses a set of scenarios with the purpose of evaluating the SIC performance when the assumptions are not guaranteed.
Autores principais:Gonçalves, A. Manuela
Outros Autores:Costa, Marco; Teixeira, Lara
Assunto:Change-point detection Environmental time series Schwarz Information Criterion (SIC) Non Gaussian data Serial correlation Simulation study
Ano:2013
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso restrito
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:A simulation study is conducted in order to assess the impact of autocorrelation and non-normality on change-point detection when it is performed by the Schwarz Information Criterion (SIC) approach. Change-point detection in environmental data is usually fulfilled in the presence of time correlation or non-Gaussian distribution. This work analyses a set of scenarios with the purpose of evaluating the SIC performance when the assumptions are not guaranteed.