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dc.contributor.author | Moret-Tatay, Carmen | es_ES |
dc.contributor.author | Gamermann, Daniel | es_ES |
dc.contributor.author | Navarro Pardo, Esperanza | es_ES |
dc.contributor.author | Fernández de Córdoba, Pedro | es_ES |
dc.date.accessioned | 2020-04-24T07:14:07Z | |
dc.date.available | 2020-04-24T07:14:07Z | |
dc.date.issued | 2018 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/141452 | |
dc.description.abstract | [EN] The 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 to multiple 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. | es_ES |
dc.description.sponsorship | This work has been financed under the Generalitat Valenciana research project GV/2016/188 (Prof. Carmen Moret-Tatay) and the Universidad Catolica de Valencia, San Vicente Martir. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Frontiers Media SA | es_ES |
dc.relation.ispartof | Frontiers in Psychology | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Response times | es_ES |
dc.subject | Response components | es_ES |
dc.subject | Python | es_ES |
dc.subject | Ex-Gaussian fit | es_ES |
dc.subject | Significance testing | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.title | ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3389/fpsyg.2018.00612 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//GV%2F2016%2F188/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Matemática Pura y Aplicada - Institut Universitari de Matemàtica Pura i Aplicada | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada | es_ES |
dc.description.bibliographicCitation | Moret-Tatay, C.; Gamermann, D.; Navarro Pardo, E.; Fernández De Córdoba, P. (2018). ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density. Frontiers in Psychology. 9:612-1-612-11. https://doi.org/10.3389/fpsyg.2018.00612 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3389/fpsyg.2018.00612 | es_ES |
dc.description.upvformatpinicio | 612-1 | es_ES |
dc.description.upvformatpfin | 612-11 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 9 | es_ES |
dc.identifier.eissn | 1664-1078 | es_ES |
dc.relation.pasarela | S\361422 | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |
dc.contributor.funder | Universidad Católica de Valencia San Vicente Mártir | es_ES |
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