ECATI - Atas de Conferências Internacionais

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http://hdl.handle.net/10437/10711

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Percorrer ECATI - Atas de Conferências Internacionais por assunto "ESTATÍSTICA MULTIVARIADA"

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    A method for detecting statistically significant differences in EEG data
    (OHBM, 2017) Fachada, Nuno; Cruz, Janir R. da; Herzog, Michael H.; Figueiredo, Patrícia; Rosa, Agostinho C.; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    The highly multivariate nature of EEG data often limits the search for statistically significant differences in data collected from two or more groups of subjects. We have recently developed a new technique for assessing whether two or more multidimensional samples are drawn from the same distribution. Here, we apply this to EEG data collected from schizophrenia patients and healthy controls while performing a Visual Backward Masking (VBM) task.
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    micompm: A MATLAB/Octave toolbox for multivariate independent comparison of observations
    (JOSS, 2018) Fachada, Nuno; Rosa, Agostinho C.; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    micompm is a MATLAB / GNU Octave port of the original micompr R package for comparing multivariate samples associated with different groups. Its purpose is to determine if the compared samples are significantly different from a statistical point of view. This method uses principal component analysis to convert multivariate observations into a set of linearly uncorrelated statistical measures, which are then compared using statistical tests and score plots. This technique is independent of the distributional properties of samples and automatically selects features that best explain their differences, avoiding manual selection of specific points or summary statistics. The procedure is appropriate for comparing samples of time series, images, spectrometric measures or similar multivariate observations. It is aimed at researchers from all fields of science, although it requires some knowledge on design of experiments, statistical testing and multidimensional data analysis.