<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0121-7488</journal-id>
<journal-title><![CDATA[Ciencia en Desarrollo]]></journal-title>
<abbrev-journal-title><![CDATA[Ciencia en Desarrollo]]></abbrev-journal-title>
<issn>0121-7488</issn>
<publisher>
<publisher-name><![CDATA[Universidad Pedagógica y Tecnológica de Colombia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0121-74882019000100067</article-id>
<article-id pub-id-type="doi">10.19053/01217488.v10.n1.2019.7261</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Uso del Método "Combinación de Riesgos" para estimar la función de supervivencia en presencia de riesgos competitivos dependientes: Un estudio de simulación]]></article-title>
<article-title xml:lang="en"><![CDATA[Using the "Risk Combination" method to estimate the survival function in the presence of competing risks dependent: A simulation study]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Bru-Cordero]]></surname>
<given-names><![CDATA[Osnamir E.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Jaramillo-Elorza]]></surname>
<given-names><![CDATA[Mario C.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional de Colombia  ]]></institution>
<addr-line><![CDATA[Sede Medellín ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Nacional de Colombia  ]]></institution>
<addr-line><![CDATA[Sede Medellín ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2019</year>
</pub-date>
<volume>10</volume>
<numero>1</numero>
<fpage>67</fpage>
<lpage>77</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0121-74882019000100067&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0121-74882019000100067&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0121-74882019000100067&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En este trabajo se comparan distintas estructuras de dependencia para los riegos que compiten en un modelo de riesgos competitivos dependientes trivariado, haciendo uso de las técnicas C-Vines y D-Vines cópulas, vía simulación estadística. Los Vines permiten obtener flexibilidad multivariada y son capaces de capturar todo el rango posible de dependencias entre los riegos competitivos, las cuales son de gran interés en los mercados financieros, problemas sociales, genéticos, entre otros. Seguidamente, se estima la función de sobrevivencia para el tiempo mínimo, tanto para el caso independiente, por medio del estimador Kaplan Meier, como para el caso dependiente, en el que usaremos el método de combinación de riesgos, el cual es una extensión del estimador cópula gráfico. Los C-D Vines cópulas, trabajan con una variedad de cópulas bivariadas, las cuales se pueden seleccionar de manera independiente y permiten tener una amplia gama de posibilidades para la caracterización de la dependencia de los riesgos que compiten, se estudian casos particulares donde dos de los tres riesgos tienen igual dependencia y el riesgo restante es independiente a los anteriores. También se estudia el caso donde dos riesgos presentan igual dependencia y el otro con dependencia alta. Además se analiza un caso particular donde los tres riesgos presentan distinta dependencia. En todos los casos estudiados, el método de combinación de riesgos es una buena alternativa para estimar las funciones de distribución marginal y la función de sobrevivencia cuando se tiene dependencia entre los riesgos de un modelo de riesgos competitivos dependientes.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract In this paper we compare different structures of dependence for the risks that compete in a trivariate competing risk model, using the C-Vines and D-Vines copula techniques, through statistical simulation. The vines can obtain multivariate flexibility and are able to capture all the possible range of dependencies between the competing risks, which are of great interest in financial markets, social, genetic among others problems. Then, we estimated survival function for the minimum time, both for the independent case, through the Kaplan Meier estimator and for the dependent case, in which we will use the risk combination method, which is an extension of the copula graphic estimator. The C-DVines copulas work with a cascade of bivariate copulas, which can be selected independently and allow a wide range of possibilities for characterizing the dependence of competing risks, we study particular cases where two of the three risks have equal dependence and the remaining risk is independent to the previous ones. We also study the case where two risks are equally dependent and the other is highly dependent. In addition, a particular case where the three risks have different dependence is analyzed. In all the cases studied, the risk combination method is a good alternative to estimate the marginal distribution functions and the survival function when there is a dependence between the risks of a dependent competing risks model.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[C-Vines]]></kwd>
<kwd lng="es"><![CDATA[D-Vines]]></kwd>
<kwd lng="es"><![CDATA[Combinación de Riesgos]]></kwd>
<kwd lng="es"><![CDATA[Cópula Gráfico]]></kwd>
<kwd lng="en"><![CDATA[C-Vines]]></kwd>
<kwd lng="en"><![CDATA[D-Vines]]></kwd>
<kwd lng="en"><![CDATA[Risk pooling method]]></kwd>
<kwd lng="en"><![CDATA[Copula Graphic]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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