<?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>1405-7743</journal-id>
<journal-title><![CDATA[Ingeniería, investigación y tecnología]]></journal-title>
<abbrev-journal-title><![CDATA[Ing. invest. y tecnol.]]></abbrev-journal-title>
<issn>1405-7743</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Facultad de Ingeniería]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-77432005000100013</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Análisis de eficiencia de la distribución Bi-Gumbel]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Escalante-Sandoval]]></surname>
<given-names><![CDATA[C.A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,UNAM Facultad de Ingeniería División de Estudios de Posgrado]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2005</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2005</year>
</pub-date>
<volume>6</volume>
<numero>1</numero>
<fpage>13</fpage>
<lpage>17</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-77432005000100013&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-77432005000100013&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-77432005000100013&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La mayoría de los estudios sobre eventos hidrológicos extremos se han llevado a cabo utilizando distribuciones univariadas. La gran variabilidad de los eventos estimados para ciertos períodos de retorno ha promovido la exploración de modelos de estimación conjunta, tal como la distribución bivariada con marginales de valores extremos tipo I, llamada Bi-Gumbel. Se emplea la técnica de muestreo distribucional con el propósito de determinar si los eventos estimados mediante el ajuste de la distribución bivariada son mejores que aquellos obtenidos en forma univariada. Se concluye que los eventos obtenidos en forma bivariada son menos sesgados que su contraparte univariada.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Most hydrological extreme studies in the past have been analyzed through use of univariate distributions. The large variability of the T-year flood estimates has prompted exploration of joint estimation models, such as the bivariate distribution with extreme value type I marginals, named Bi-Gumbel distribution. To investigate whether the estimates of the quantiles based on bivariate ditribution are better than those on univariate procedures a distribution sampling technique was used. A significant improvement occurs when the parameters are estimated using the bivariate distribution instead of univariate form and such again is more significant in relation to the shorter samples.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Distribución multivariada de valores extremos]]></kwd>
<kwd lng="es"><![CDATA[distribución Gumbel]]></kwd>
<kwd lng="es"><![CDATA[estimados de máxima verosimilitud]]></kwd>
<kwd lng="es"><![CDATA[técnica de muestreo distribucional]]></kwd>
<kwd lng="en"><![CDATA[Multivariate extreme value distribution]]></kwd>
<kwd lng="en"><![CDATA[Gumbel distribution]]></kwd>
<kwd lng="en"><![CDATA[maximum like lihood estimates]]></kwd>
<kwd lng="en"><![CDATA[distribution sampling technique]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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