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dc.contributor.authorMoret-Tatay, Carmenpt_BR
dc.contributor.authorGamermann, Danielpt_BR
dc.contributor.authorNavarro-Pardo, Esperanzapt_BR
dc.contributor.authorFernández de Córdoba, Pedro‏pt_BR
dc.date.accessioned2018-09-18T02:30:12Zpt_BR
dc.date.issued2018pt_BR
dc.identifier.issn1664-1078pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/182118pt_BR
dc.description.abstractThe study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are often modeled through the ex-Gaussian distribution, because it provides a good fit tomultiple empirical data. The complexity of this distribution makes the use of computational tools an essential element. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex-Gaussian probability density. In order to validate the package, we present an extensive analysis of fits obtained with it, discuss advantages and differences between the least squares and maximum likelihood methods and quantitatively evaluate the goodness of the obtained fits (which is usually an overlooked point in most literature in the area). The analysis done allows one to identify outliers in the empirical datasets and criteriously determine if there is a need for data trimming and at which points it should be done.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofFrontiers in Psychology. Lausanne. Vol. 9, (May 2018), 612, 11 p.pt_BR
dc.rightsOpen Accessen
dc.subjectResponse timesen
dc.subjectTempo de reaçãopt_BR
dc.subjectResponse componentsen
dc.subjectAnálise estatísticapt_BR
dc.subjectDistribuição Gaussianapt_BR
dc.subjectPythonen
dc.subjectEx-Gaussian fiten
dc.subjectSignificance testingen
dc.titleExGUtils : a Python package for statistical analysis with the ex-Gaussian probability densitypt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001072908pt_BR
dc.type.originEstrangeiropt_BR


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