dc.contributor | Urdinola Contreras, Beatriz Piedad | |
dc.creator | Gómez Lizarazú, David Eduardo | |
dc.date.accessioned | 2020-07-24T16:40:43Z | |
dc.date.available | 2020-07-24T16:40:43Z | |
dc.date.created | 2020-07-24T16:40:43Z | |
dc.date.issued | 2019-12-01 | |
dc.identifier | Gómez, D. (2020). Comparación del comportamiento estadístico de índices de concentración en salud ante la presencia de contaminación en los datos. Tesis de maestría. Universidad Nacional de Colombia. | |
dc.identifier | https://repositorio.unal.edu.co/handle/unal/77847 | |
dc.description.abstract | Esta tesis busca responder a la pregunta de investigación ¿qué tan sensibles son los índices de concentración en salud a la contaminación en los datos y qué implicaciones tiene dicha sensibilidad sobre las propiedades estadísticas de los índices? Se propone una extensión al trabajo de Cowell & Flachaire (2007), quienes muestran que en el caso univariado las medidas de desigualdad presentan alta sensibilidad a la presencia de datos extremos y que, adicionalmente, se puede ver afectada la validez de la pruebas de hipótesis sobre los estimadores calculados a partir de estas muestras cuando hay datos atípicos en las mismas. Para extender los resultados de Cowell & Flachaire (2007) a índices de concentración en salud se utilizan algunas de las Funciones de Influencia calculadas por Heckley et al. (2016); las Funciones de Influencia son tomadas de la teoría de la estadística robusta y se constituyen en la principal herramienta que se usará para extender los hallazgos del caso univariado al caso bivariado. Adicionalmente se utiliza la conexión existente entre Funciones de Influencia y la estadística no paramétrica para analizar en un marco teórico unificado el comportamiento de los índices de concentración, entendidos estos como Estadisticos-V (Heckley et al., 2016). | |
dc.description.abstract | This thesis seeks to answer the research question: how sensitive are health concentration indices when there are contamination in the data and what kind of implications does this sensitivity have on the statistical properties of the indices? We follow the work of Cowell & Flachaire (2007), who show that in the univariate case the inequality measures present high sensitivity to the presence of extreme data and that, in addition, the validity of the hypothesis testing on the estimators can be affected. To extend the results of Cowell & Flachaire (2007) to health concentration indices, some of the Influence Functions calculated by Heckley et al. (2016) this document uses; Influence Functions are taken from the theory of robust statistics and they are the main tool that will be used to extend the findings of the univariate case to the bivariate case. In addition, it is used the link between Nonparametric statistics and the Influences Functions in order to analyse in a unified theory framework the behaivour of the health concentration indexes which are V-Statistics (Heckley et al., 2016) | |
dc.language | spa | |
dc.publisher | Bogotá - Ciencias - Maestría en Ciencias - Estadística | |
dc.publisher | Departamento de Estadística | |
dc.publisher | Universidad Nacional de Colombia - Sede Bogotá | |
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dc.rights | Atribución-NoComercial 4.0 Internacional | |
dc.rights | Acceso abierto | |
dc.rights | http://creativecommons.org/licenses/by-nc/4.0/ | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.rights | Derechos reservados - Universidad Nacional de Colombia | |
dc.title | Comparación del comportamiento estadístico de índices de concentración en salud ante la presencia de contaminación en los datos | |
dc.type | Otro | |