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Modelo estadístico para el análisis de variables negativas con aplicación a pruebas de contracción en concreto

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dc.contributor.authorUsuga, Olgaspa
dc.contributor.authorPatiño Rodríguez, Carmenspa
dc.contributor.authorHernández Barajas, Freddyspa
dc.contributor.authorUrrea Montoya, Amylkarspa
dc.date.accessioned2022-06-01 00:00:00
dc.date.accessioned2022-06-17T20:21:25Z
dc.date.available2022-06-01 00:00:00
dc.date.available2022-06-17T20:21:25Z
dc.date.issued2022-06-01
dc.description.abstractEn algunas áreas de conocimiento se pueden presentar fenómenos que son representados por variables aleatorias negativas (ℝ-) ; contar con un modelo estadístico es crucial para representar esos fenómenos y explicarlos en función de otras variables auxiliares. En este trabajo se propone un modelo de regresión para el análisis de variables aleatorias negativas tomando como distribución para la variable respuesta la distribución Weibull reflejada. En este artículo reportamos el paquete RelDists creado en el lenguaje de programación R para facilitar el uso del modelo de regresión propuesto. Por medio de un estudio de simulación Monte Carlo se exploró el desempeño del proceso de estimación de parámetros. En el estudio de simulación se consideraron dos casos: sin covariables y con covariables. El primer caso se refiere a la situación en la cual sólo se tiene la variable respuesta y con ella se deben estimar los parámetros de la distribución. En el segundo caso se tiene la variable respuesta y variables explicativas que en conjunto se usan para estimar los parámetros del modelo de regresión. Adicionalmente, en el estudio de simulación se consideraron datos censurados y no censurados. Del estudio se encontró que el proceso de estimación logra estimar bien los parámetros del modelo a medida que el tamaño de la muestra aumenta y que el porcentaje de censura disminuye. En el artículo se muestra una aplicación del modelo propuesto usando datos experimentales provenientes de una prueba de contracción con probetas de concreto. En la aplicación se construyó un modelo para explicar la contracción de las probetas en función del tiempo. El modelo de regresión para variables aleatorias negativa y el paquete RelDists pueden ser usados por comunidades académicas, científicas y de negocios para el desarrollo de análisis de confiabilidad.spa
dc.description.abstractIn some areas of knowledge, we can find negative variables (ℝ-), to have a statistical model is crucial to represent the phenomenon and explain it using other variables. This paper proposes a regression model to analyze negative random variables using the reflected Weibull distribution. We developed the RelDists package in the R programming language to implement the proposed model. A Monte Carlo simulation study was conducted to explore the performance of the estimation procedure considering censored and uncensored data and the presence and absence of covariates. From the simulation study, we found that the estimation procedure achieves accurate estimations of the parameters as the sample size increases and the percentage of censoring decreases. In the paper, we present an application of the proposed model using experimental data from a compression test with concrete specimens. In the application, a model was fitted to explain the shrinkage strain using the variable time. The regression model for negative variables and the RelDists package can be used by academic, scientific, and business communities to perform reliability analysis.eng
dc.format.mimetypeapplication/pdfeng
dc.identifier.doi10.24050/reia.v19i38.1526
dc.identifier.eissn2463-0950
dc.identifier.issn1794-1237
dc.identifier.urihttps://repository.eia.edu.co/handle/11190/5166
dc.identifier.urlhttps://doi.org/10.24050/reia.v19i38.1526
dc.language.isoengeng
dc.publisherFondo Editorial EIA - Universidad EIAspa
dc.relation.bitstreamhttps://revistas.eia.edu.co/index.php/reveia/article/download/1526/1454
dc.relation.citationeditionNúm. 38 , Año 2022 : .spa
dc.relation.citationendpage19
dc.relation.citationissue38spa
dc.relation.citationstartpage3806 pp. 1
dc.relation.citationvolume19spa
dc.relation.ispartofjournalRevista EIAspa
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dc.rightsRevista EIA - 2022eng
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesseng
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2eng
dc.rights.creativecommonsEsta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.eng
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0eng
dc.sourcehttps://revistas.eia.edu.co/index.php/reveia/article/view/1526eng
dc.subjectReflected Weibulleng
dc.subjectRegression modeleng
dc.subjectGAMLSSeng
dc.subjectCompression test on concreteeng
dc.subjectconfiabilidadspa
dc.subjectdatos censuradosspa
dc.subjectestimación de parámetrosspa
dc.subjectGAMLSSspa
dc.subjectenguaje de programación Rspa
dc.subjectmáxima verosimilitudspa
dc.subjectmodelo de regresiónspa
dc.subjectprueba de contracción en concretospa
dc.subjectvariable aleatoria negativaspa
dc.subjectWeibull reflejadaspa
dc.titleModelo estadístico para el análisis de variables negativas con aplicación a pruebas de contracción en concretospa
dc.title.translatedStatistical model for analizing negative variables with application to compression test on concreteeng
dc.typeArtículo de revistaspa
dc.typeJournal articleeng
dc.type.coarhttp://purl.org/coar/resource_type/c_6501eng
dc.type.coarhttp://purl.org/coar/resource_type/c_6501eng
dc.type.coarversionhttp://purl.org/coar/version/c_970fb48d4fbd8a85eng
dc.type.contentTexteng
dc.type.driverinfo:eu-repo/semantics/articleeng
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTREFeng
dc.type.versioninfo:eu-repo/semantics/publishedVersioneng
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