<?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>2007-2422</journal-id>
<journal-title><![CDATA[Tecnología y ciencias del agua]]></journal-title>
<abbrev-journal-title><![CDATA[Tecnol. cienc. agua]]></abbrev-journal-title>
<issn>2007-2422</issn>
<publisher>
<publisher-name><![CDATA[Instituto Mexicano de Tecnología del Agua, Coordinación de Comunicación, Participación e Información]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2007-24222021000200442</article-id>
<article-id pub-id-type="doi">10.24850/j-tyca-2021-02-10</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Ajuste de la distribución de valores extremos de dos componentes (TCEV) por medio de máxima verosimilitud]]></article-title>
<article-title xml:lang="en"><![CDATA[Fit of the two-component extreme value (TCEV) distribution through of maximum likelihood]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Campos-Aranda]]></surname>
<given-names><![CDATA[Daniel Francisco]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma de San Luis Potosí  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2021</year>
</pub-date>
<volume>12</volume>
<numero>2</numero>
<fpage>442</fpage>
<lpage>489</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-24222021000200442&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-24222021000200442&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-24222021000200442&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En muchas cuencas medianas y grandes de nuestro país y del mundo, su registro anual de crecientes está integrado por eventos que fueron generados por fenómenos físicamente diferentes. Por ejemplo, muchas crecientes se originan con tormentas locales y una porción pequeña se debe a lluvias ciclónicas de amplia cobertura y duración, que generan crecientes extraordinarias. Para este tipo de registros se propone la distribución TCEV (two-component extreme value) con cuatro parámetros de ajuste, la cual tiene una base teórica que permite una interpretación aproximada para dos mecanismos de generación de las crecientes y que además es capaz de reproducir la variabilidad real del coeficiente de asimetría. En este trabajo se detalla su génesis y el método de ajuste por máxima verosimilitud, según dos versiones numéricas: (1) sustitución sucesiva y (2) maximización de la función objetivo. Se procesaron seis registros de crecientes, cuya amplitud varió de 31 a 72 datos, con tres a seis valores dispersos o crecientes que se apartan de la tendencia general. Se contrastan las predicciones del modelo TCEV, ajustado con cada método numérico, contra las obtenidas con las distribuciones de aplicación establecida bajo precepto (LP3, GVE y LOG) y la Wakeby. Aceptando el error estándar de ajuste como criterio de selección, se deduce que la distribución TCEV es la mejor opción en dos de los seis registros procesados. Por último, se formulan las conclusiones, las cuales sugieren la aplicación sistemática de la distribución TCEV con ambos métodos numéricos en los registros que presentan dos poblaciones mezcladas.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The annual record of floods, in many medium and large basins of our country and the world, is made up of events generated by phenomena which are physically different. For example, many floods originate from local storms, and a small portion is generated by cyclonic rains with a wide coverage and long duration, which generate extraordinary floods. The TCEV (two-component extreme value) distribution with four fitting parameters has been proposed for this type of records. TCEV has a theoretical basis that allows an approximate interpretation for two flood generation mechanisms, and it is also capable of reproducing the real variability of the asymmetry coefficient. This paper details its genesis and the fitting method by maximum likelihood, according to two numerical versions: (1) successive substitution and (2) objective function maximization. Six flood records were processed, the amplitude of which varied from 31 to 72 data, with three to six outliers or floods values that depart from the general trend. The predictions of the TCEV model, fitted with both numerical methods, are compared with those obtained using the standard application distributions (LP3, GVE and LOG) and the Wakeby distribution. Accepting the standard error of fit as a selection criterion, it follows that TCEV distribution is the best option in two of the six records processed. Lastly, as a conclusion, the systematic application of the TCEV distribution is suggested, using both numerical methods, in records with two mixed populations.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[distribución TCEV]]></kwd>
<kwd lng="es"><![CDATA[proceso de Poisson]]></kwd>
<kwd lng="es"><![CDATA[máxima verosimilitud]]></kwd>
<kwd lng="es"><![CDATA[algoritmo de Rosenbrock]]></kwd>
<kwd lng="es"><![CDATA[error estándar de ajuste]]></kwd>
<kwd lng="es"><![CDATA[homogeneidad y estacionariedad]]></kwd>
<kwd lng="es"><![CDATA[contraste de predicciones]]></kwd>
<kwd lng="en"><![CDATA[TCEV distribution]]></kwd>
<kwd lng="en"><![CDATA[Poisson process]]></kwd>
<kwd lng="en"><![CDATA[maximum likelihood]]></kwd>
<kwd lng="en"><![CDATA[Rosenbrock algorithm]]></kwd>
<kwd lng="en"><![CDATA[standard error of fit]]></kwd>
<kwd lng="en"><![CDATA[homogeneity and stationarity]]></kwd>
<kwd lng="en"><![CDATA[prediction contrast]]></kwd>
</kwd-group>
</article-meta>
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