<?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>S0120-17512008000100001</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Test de hipótesis para contrastar la igualdad entre k-poblaciones]]></article-title>
<article-title xml:lang="en"><![CDATA[Hypothesis Test to Compare the Equality Among k-populations]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[MARTÍNEZ-CAMBLOR]]></surname>
<given-names><![CDATA[PABLO]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,Fundación Caubet-Cimera Illes Balears  ]]></institution>
<addr-line><![CDATA[Mallorca ]]></addr-line>
<country>España</country>
</aff>
<pub-date pub-type="pub">
<day>15</day>
<month>06</month>
<year>2008</year>
</pub-date>
<pub-date pub-type="epub">
<day>15</day>
<month>06</month>
<year>2008</year>
</pub-date>
<volume>31</volume>
<numero>1</numero>
<fpage>1</fpage>
<lpage>18</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0120-17512008000100001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0120-17512008000100001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0120-17512008000100001&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Este trabajo estudia las ventajas y limitaciones de un test para contrastar la igualdad de las distribuciones de origen de k-muestras independientes. El estadístico propuesto, denominado LGk, está basado en una medida que generaliza la norma L1 entre funciones de densidad y que permite comparar simultáneamente k densidades. Desde esta medida y a partir de la estimación kernel, se desarrolla un test para contrastes de igualdad entre k poblaciones independientes (LGk). A partir de un "amplio" estudio de simulación, se estudia la potencia del test propuesto y se compara con algunos de los test no paramétricos ya existentes, considerando ocho estadísticos diferentes. También se analiza el tema de la elección del tamaño del parámetro ventana y se realizan algunas propuestas relativas a este problema.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[In this paper we study a test to contrast the equality among the origen distributions of k-independent samples. The proposed statistic, denoted as LGk, is based in a measure which generalizes the L1-norm among density functions and it allows us to compare k-different densities. From this measure and the kernel density estimation, a k-sample test for independent populations is developed. We make a wide simulation study for the proposed test and we compare its power with other nonparametric k-sample test, by considering a total of eight different statistics. We also analyze the topic of the bandwidth selection and make the same proposals about this problem.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[estimación kernel]]></kwd>
<kwd lng="es"><![CDATA[medida L1]]></kwd>
<kwd lng="es"><![CDATA[selección del parámetro ventana]]></kwd>
<kwd lng="es"><![CDATA[bootstrap]]></kwd>
<kwd lng="en"><![CDATA[Kernel density estimation]]></kwd>
<kwd lng="en"><![CDATA[L1 Measure]]></kwd>
<kwd lng="en"><![CDATA[Bandwidth selection]]></kwd>
<kwd lng="en"><![CDATA[Bootstrap]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[  <font size="2" face="verdana">      <p> <b> <font size="4">     <center> Test de hip&oacute;tesis para contrastar la igualdad entre <b>k</b>-poblaciones </center> </font> </b> </p>      <p> <b> <font size="3">     <center> Hypothesis Test to Compare the Equality Among <b>k</b>-populations </center> </font> </b> </p>      <p>     <center> PABLO MART&Iacute;NEZ-CAMBLOR<sup>1</sup> </center> </p>      <p> <sup>1</sup>Fundaci&oacute;n Caubet-Cimera Illes Balears, Mallorca, Espa&ntilde;a. Programa de epidemiolog&iacute;a e investigaci&oacute;n cl&iacute;nica. Email: <a href="mailto:martinez@caubet-cimera.es">martinez@caubet-cimera.es</a>     <br> </p>  <hr size="1">      <p> <b>     ]]></body>
<body><![CDATA[<center> Resumen </center> </b> </p>      <p> Este trabajo estudia las ventajas y limitaciones de un test para contrastar la igualdad de las distribuciones de origen de k-muestras independientes. El estad&iacute;stico propuesto, denominado LG<sub>k</sub>, est&aacute; basado en una medida que generaliza la norma L<sub>1</sub> entre funciones de densidad y que permite comparar simult&aacute;neamente k densidades. Desde esta medida y a partir de la estimaci&oacute;n <i>kernel</i>, se desarrolla un test para contrastes de igualdad entre k poblaciones independientes (LG<sub>k</sub>). A partir de un &quot;amplio&quot; estudio de simulaci&oacute;n, se estudia la potencia del test propuesto y se compara con algunos de los test no param&eacute;tricos ya existentes, considerando ocho estad&iacute;sticos diferentes. Tambi&eacute;n se analiza el tema de la elecci&oacute;n del tama&ntilde;o del par&aacute;metro ventana y se realizan algunas propuestas relativas a este problema. </p>      <p> <b> Palabras clave: </b> estimaci&oacute;n <i>kernel</i>, medida L<sub>1</sub>, selecci&oacute;n del par&aacute;metro ventana, <i>bootstrap</i>. </p>  <hr size="1">      <p> <b>     <center> Abstract </center> </b> </p>      <p> In this paper we study a test to contrast the equality among the origen distributions of k-independent samples. The proposed statistic, denoted as LG<sub>k</sub>, is based in a measure which generalizes the L<sub>1</sub>-norm among density functions and it allows us to compare k-different densities. From this measure and the <i>kernel</i> density estimation, a k-sample test for independent populations is developed. We make a wide simulation study for the proposed test and we compare its power with other nonparametric k-sample test, by considering a total of eight different statistics. We also analyze the topic of the bandwidth selection and make the same proposals about this problem. </p>      <p> <b> Key words: </b> Kernel density estimation, L<sub>1</sub> Measure, Bandwidth selection, Bootstrap. </p>  <hr size="1">      <p> Texto completo disponible en <a href="pdf/rce/v31n1/v31n1a01.pdf">PDF</a> </p>  <hr size="1">      <p> <b> <font size="3"> Referencias </font> </b> </p>       <!-- ref --><p> 1. Anderson, N. H., Hall, P. & Titterington, D. M. (1994), `Two-Sample Test Statistics for Measuring Discrepancies Between Two Multivariate Probability Density Functions using Kernel-Based Density Estimates´, <i>Journal of Multivariate Analysis</i> <b>50</b>, 41-54. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000022&pid=S0120-1751200800010000100001&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p> 2. Cao, R. & Van Keilegom, I. (2006), `Empirical Likelihood Tests for Two-Sample Problems via Nonparametric Density Estimation´, <i>Canad. J. 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(1952), `Use of Ranks in One-Criterion Variance Analysis´, <i>Journal of the American Statistical Association</i> <b>47</b>(260), 583-621. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000029&pid=S0120-1751200800010000100008&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p> 9. Lewis, J. L. (1972), `A k-Sample Test Based on Range Intervals´, <i>Biometrika</i> <b>59</b>(1), 155-160. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000030&pid=S0120-1751200800010000100009&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p> 10. Nadaraya, E. A. (1964), `Some new Estimates for Distribution Functions´, <i>Theory Prob. 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(1986), <i>Density Estimation for Statistics and Data Analysis</i>, Chapman & Hall, London, United Kingdom. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000035&pid=S0120-1751200800010000100014&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p> 15. Wand, M. P. & Jones, M. C. (1995), <i>Kernel Smoothing</i>, Chapman & Hall, London, United Kingdom. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000036&pid=S0120-1751200800010000100015&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p> 16. Zhang, J. & Wu, Y. (2007), `K-Sample Tests Based on the Likelihood Ratio´, <i>Comput. Stat. Data Anal.</i> <b>51</b>(9), 4682-4691. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000037&pid=S0120-1751200800010000100016&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><center> <b>&#91;Recibido en junio de 2007. Aceptado en agosto de 2007&#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{RCEv31n1a01,    <br>  &nbsp;&nbsp;&nbsp; AUTHOR &nbsp;= {Mart&iacute;nez-Camblor, Pablo},    <br>  &nbsp;&nbsp;&nbsp; TITLE &nbsp; = {{Test de hip&oacute;tesis para contrastar la igualdad entre <b>k</b>-poblaciones}},    <br>  &nbsp;&nbsp;&nbsp; JOURNAL = {Revista Colombiana de Estad&iacute;stica},    ]]></body>
<body><![CDATA[<br> &nbsp;&nbsp;&nbsp; YEAR &nbsp;&nbsp; = {2008},    <br> &nbsp;&nbsp;&nbsp; volume &nbsp;= {31},    <br> &nbsp;&nbsp;&nbsp; number &nbsp;= {1},    <br> &nbsp;&nbsp;&nbsp; pages &nbsp; = {1-18}    <br> }</font></code>  <hr size="1"> </font>      ]]></body><back>
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