<?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>0120-1751</journal-id>
<journal-title><![CDATA[Revista Colombiana de Estadística]]></journal-title>
<abbrev-journal-title><![CDATA[Rev.Colomb.Estad.]]></abbrev-journal-title>
<issn>0120-1751</issn>
<publisher>
<publisher-name><![CDATA[Departamento de Estadística - Universidad Nacional de Colombia.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0120-17512011000300010</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[On Certain Properties of A Class of Bivariate Compound Poisson Distributions and an Application to Earthquake Data]]></article-title>
<article-title xml:lang="es"><![CDATA[Ciertas propiedades de una clase de distribuciones Poisson compuesta bivariadas y una aplicación a datos de terremotos]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[ÖZEL]]></surname>
<given-names><![CDATA[GAMZE]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,Hacettepe University Department of Statistics ]]></institution>
<addr-line><![CDATA[Ankara ]]></addr-line>
<country>Turkey</country>
</aff>
<pub-date pub-type="pub">
<day>15</day>
<month>12</month>
<year>2011</year>
</pub-date>
<pub-date pub-type="epub">
<day>15</day>
<month>12</month>
<year>2011</year>
</pub-date>
<volume>34</volume>
<numero>3</numero>
<fpage>545</fpage>
<lpage>566</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0120-17512011000300010&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0120-17512011000300010&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0120-17512011000300010&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[The univariate compound Poisson distribution has many applications in various areas such as biology, seismology, risk theory, forestry, health science, etc. In this paper, a bivariate compound Poisson distribution is proposed and the joint probability function of this model is derived. Expressions for the product moments, cumulants, covariance and correlation coefficient are also obtained. Then, an algorithm is prepared in Maple to obtain the probabilities quickly and an empirical comparison of the proposed probability function is given. Bivariate versions of the Neyman type A, Neyman type B, geometric-Poisson, Thomas distributions are introduced and the usefulness of these distributions is illustrated in the analysis of earthquake data.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[La distribución compuesta de Poisson univariada tiene muchas aplicaciones en diversas áreas tales como biología, ciencias de la salud, ingeniería forestal, sismología y teoría del riesgo, entre otras. En este artículo, una distribución compuesta de Poisson bivariada es propuesta y la función de probabilidad conjunta de este modelo es derivada. Expresiones para los momentos producto, acumuladas, covarianza y el coeficiente de correlación respectivos son obtenidas. Finalmente, un algoritmo preparado en lenguaje Maple es descrito con el fin de calcular probabilidades asociadas rápidamente y con el fin de hacer una comparación de la función de probabilidad propuesta. Se introducen además versiones bivariadas de las distribuciones tipo A y tipo B de Neyman, geométrica-Poisson y de Thomas y se ilustra la utilidad de estas distribuciones aplicadas al análisis de datos de terremoto.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Bivariate distribution]]></kwd>
<kwd lng="en"><![CDATA[Coefficient of correlation]]></kwd>
<kwd lng="en"><![CDATA[Compound Poisson distribution]]></kwd>
<kwd lng="en"><![CDATA[Cumulant]]></kwd>
<kwd lng="en"><![CDATA[Moment]]></kwd>
<kwd lng="es"><![CDATA[coeficiente de correlación]]></kwd>
<kwd lng="es"><![CDATA[conjuntas]]></kwd>
<kwd lng="es"><![CDATA[distribución bivariada]]></kwd>
<kwd lng="es"><![CDATA[distribución compuesta de Poisson]]></kwd>
<kwd lng="es"><![CDATA[momento]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[  <font size="2" face="verdana">      <p> <b> <font size="4">     <center> On Certain Properties of A Class of Bivariate Compound Poisson Distributions and an Application to Earthquake Data </center> </font> </b> </p>      <p> <b> <font size="3">     <center> Ciertas propiedades de una clase de distribuciones Poisson compuesta bivariadas y una aplicaci&oacute;n a datos de terremotos </center> </font> </b> </p>      <p>     <center> GAMZE &Ouml;ZEL<sup>1</sup> </center> </p>      <p> <sup>1</sup>Hacettepe University, Department of Statistics, Ankara, Turkey. Doctor. Email: <a href="mailto:gamzeozl@hacettepe.edu.tr">gamzeozl@hacettepe.edu.tr</a>     <br> </p>  <hr size="1">      <p> <b>     ]]></body>
<body><![CDATA[<center> Abstract </center> </b> </p>      <p> The univariate compound Poisson distribution has many applications in various areas such as biology, seismology, risk theory, forestry, health science, etc. In this paper, a bivariate compound Poisson distribution is proposed and the joint probability function of this model is derived. Expressions for the product moments, cumulants, covariance and correlation coefficient are also obtained. Then, an algorithm is prepared in Maple to obtain the probabilities quickly and an empirical comparison of the proposed probability function is given. Bivariate versions of the Neyman type A, Neyman type B, geometric-Poisson, Thomas distributions are introduced and the usefulness of these distributions is illustrated in the analysis of earthquake data. </p>      <p> <b> Key words: </b> Bivariate distribution, Coefficient of correlation, Compound Poisson distribution, Cumulant, Moment. </p>  <hr size="1">      <p> <b>     <center> Resumen </center> </b> </p>      <p> La distribuci&oacute;n compuesta de Poisson univariada tiene muchas aplicaciones en diversas &aacute;reas tales como biolog&iacute;a, ciencias de la salud, ingenier&iacute;a forestal, sismolog&iacute;a y teor&iacute;a del riesgo, entre otras. En este art&iacute;culo, una distribuci&oacute;n compuesta de Poisson bivariada es propuesta y la funci&oacute;n de probabilidad conjunta de este modelo es derivada. Expresiones para los momentos producto, acumuladas, covarianza y el coeficiente de correlaci&oacute;n respectivos son obtenidas. Finalmente, un algoritmo preparado en lenguaje Maple es descrito con el fin de calcular probabilidades asociadas r&aacute;pidamente y con el fin de hacer una comparaci&oacute;n de la funci&oacute;n de probabilidad propuesta. Se introducen adem&aacute;s versiones bivariadas de las distribuciones tipo A y tipo B de Neyman, geom&eacute;trica-Poisson y de Thomas y se ilustra la utilidad de estas distribuciones aplicadas al an&aacute;lisis de datos de terremoto. </p>      <p> <b> Palabras clave: </b> coeficiente de correlaci&oacute;n, conjuntas, distribuci&oacute;n bivariada, distribuci&oacute;n compuesta de Poisson, momento. </p>  <hr size="1">      <p> Texto completo disponible en <a href="pdf/rce/v34n3/v34n3a10.pdf">PDF</a> </p>  <hr size="1">      <p> <b> <font size="3"> References </font> </b> </p>       <!-- ref --><p> 1. Agnew, D. C. & Jones, L. M. 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(1992), 'On some extensions of Panjer's class of counting distributions', <i>ASTIN Bulletin</i> <b>22</b>, 61-80.    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000066&pid=S0120-1751201100030001000023&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --> </p>      <!-- ref --><p> 24. Wienke, A., Ripatti, S., Palmgren, J. & Yashin, A. (2010), 'A bivariate survival model with compound Poisson frailty', <i>Statistics in Medicine</i> <b>29</b>(2), 275-283.    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000068&pid=S0120-1751201100030001000024&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --> </p>  <hr size="1">      <center> <b>&#91;Recibido en febrero de 2011. Aceptado en septiembre de 2011&#93;</b> </center> <hr size="1">      <p> Este art&iacute;culo se puede citar en <i>LaTeX</i> utilizando la siguiente referencia bibliogr&aacute;fica de <i>BibTeX</i>: </p> <code><font size="2">@ARTICLE{RCEv34n3a10,    <br>  &nbsp;&nbsp;&nbsp; AUTHOR &nbsp;= {&Ouml;zel, Gamze},    ]]></body>
<body><![CDATA[<br>  &nbsp;&nbsp;&nbsp; TITLE &nbsp; = {{On Certain Properties of A Class of Bivariate Compound Poisson Distributions and an Application to Earthquake Data}},    <br>  &nbsp;&nbsp;&nbsp; JOURNAL = {Revista Colombiana de Estad&iacute;stica},    <br> &nbsp;&nbsp;&nbsp; YEAR &nbsp;&nbsp; = {2011},    <br> &nbsp;&nbsp;&nbsp; volume &nbsp;= {34},    <br> &nbsp;&nbsp;&nbsp; number &nbsp;= {3},    <br> &nbsp;&nbsp;&nbsp; pages &nbsp; = {545-566}    <br> }</font></code>  <hr size="1"> </font>      ]]></body><back>
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