<?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>1794-1237</journal-id>
<journal-title><![CDATA[Revista EIA]]></journal-title>
<abbrev-journal-title><![CDATA[Rev.EIA.Esc.Ing.Antioq]]></abbrev-journal-title>
<issn>1794-1237</issn>
<publisher>
<publisher-name><![CDATA[Escuela de ingenieria de Antioquia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1794-12372012000200003</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[AJUSTE DE CURVAS MEDIANTE MÉTODOS NO PARAMÉTRICOS PARA ESTUDIAR EL COMPORTAMIENTO DE CONTAMINACIÓN DEL AIRE POR MATERIAL PARTICULADO PM10]]></article-title>
<article-title xml:lang="en"><![CDATA[CURVE FITTING NONPARAMETRIC METHODS FOR STUDYING BEHAVIOR FROM AIR POLLUTION PM10]]></article-title>
<article-title xml:lang="pt"><![CDATA[AJUSTE DE CURVAS MEDIANTE MÉTODOS NÃO PARAMÉTRICOS PARA ESTUDAR O COMPORTAMENTO DE CONTAMINAÇÃO DO AR POR MATERIAL PARTICULADO PM10]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Reina]]></surname>
<given-names><![CDATA[Jhovana]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Olaya]]></surname>
<given-names><![CDATA[Javier]]></given-names>
</name>
<xref ref-type="aff" rid="A02"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,Universidad del Valle  ]]></institution>
<addr-line><![CDATA[Cali ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="A02">
<institution><![CDATA[,Universidad del Valle  ]]></institution>
<addr-line><![CDATA[Cali ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2012</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2012</year>
</pub-date>
<numero>18</numero>
<fpage>19</fpage>
<lpage>31</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S1794-12372012000200003&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S1794-12372012000200003&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S1794-12372012000200003&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Uno de los principales agentes contaminantes del aire es el material particulado de diámetro aerodinámico inferior a 10 micrómetros, comúnmente conocido como PM10. Su comportamiento varía de forma irregular y temporal en la atmósfera, debido a las actividades humanas, condiciones atmosféricas inestables y fenómenos meteorológicos. El propósito de este estudio es caracterizar con un modelo de suavización no paramétrica el comportamiento del PM10 en el aire a lo largo de un día, teniendo en cuenta el día de la semana y los niveles de precipitación. El modelo propuesto se ilustra con registros sobre contaminación por PM10 y con datos de precipitación en el norte de Cali, Colombia. Se estiman curvas típicas diarias del comportamiento del PM10 usando suavizadores kernel y spline. El procesamiento se ejecuta con el software estadístico de libre distribución R. Las curvas estimadas permiten observar un comportamiento unimodal del PM10 durante las horas de la mañana, diferenciado por días de la semana y por días con lluvia y sin lluvia. Los modelos permiten caracterizar de manera robusta el comportamiento diario del PM10, teniendo en cuenta observaciones heterocedásticas bajo un escenario de múltiples respuestas por punto de diseño.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[One of the main air pollutants is the particulate matter whose aerodynamic diameter is less than 10 micrometers, usually referred as PM10. It is a fact that the PM10 behavior in the air varies in an irregular way, and also in a temporal way in the atmosphere, mainly due to human activities, to unstable atmospheric conditions, and to meteorological phenomena. Our main purpose is to characterize through a nonparametric smooth model the PM10 daily behavior, taking into account the day of the week, and the precipitation levels. We illustrate the model using records on PM10 contamination, as well as on data on rain precipitation in the north side of Cali, Colombia. We estimate daily typical curves of the PM10 behavior using kernel and spline estimators. We processed these data using the free distribution statistical software R. The estimated curves allow us to observe a PM10 unimodal behavior during the morning hours, which varies from one day to another and from rainy to non-rainy days. The fitted models allow a robust characterization of the PM10 daily behavior, considering heteroscedastic observations on a multiple response per design point scenario.]]></p></abstract>
<abstract abstract-type="short" xml:lang="pt"><p><![CDATA[Um dos principais agentes contaminantes do ar é o material particulado de diâmetro aerodinâmico inferior a 10 micrômetros, comumente conhecido como PM10. Seu comportamento varia de forma irregular e temporal na atmosfera, devido às atividades humanas, condições atmosféricas instáveis e fenômenos meteorológicos. O propósito deste estudo é caracterizar com um modelo de suavização não paramétrica o comportamento do PM10 no ar ao longo de um dia, tendo em conta o dia da semana e os níveis de precipitação. O modelo proposto ilustra-se com registros sobre contaminação por PM10 e com dados de precipitação no norte de Cali, Colômbia. Estimam-se curvas típicas diárias do comportamento do PM10 usando suavizadores kernel e spline. O processamento executa-se com o software estatístico de livre distribuição R. As curvas estimadas permitem observar um comportamento unimodal do PM10 durante as horas da manhã, diferenciado por dias da semana e por dias com chuva e sem chuva. Os modelos permitem caracterizar de maneira robusta o comportamento diário do PM10, tendo em conta observações heterocedásticas baixo um cenário de múltiplas respostas por ponto de desenho.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[contaminación atmosférica]]></kwd>
<kwd lng="es"><![CDATA[heterocedasticidad]]></kwd>
<kwd lng="es"><![CDATA[PM10]]></kwd>
<kwd lng="es"><![CDATA[regresión no paramétrica]]></kwd>
<kwd lng="es"><![CDATA[suavización kernel]]></kwd>
<kwd lng="es"><![CDATA[suavización spline]]></kwd>
<kwd lng="en"><![CDATA[air pollution]]></kwd>
<kwd lng="en"><![CDATA[heteroscedasticity]]></kwd>
<kwd lng="en"><![CDATA[PM10]]></kwd>
<kwd lng="en"><![CDATA[nonparametric regression]]></kwd>
<kwd lng="en"><![CDATA[kernel smoothing]]></kwd>
<kwd lng="en"><![CDATA[spline smoothing]]></kwd>
<kwd lng="pt"><![CDATA[contaminação atmosférica]]></kwd>
<kwd lng="pt"><![CDATA[heterocedasticidade]]></kwd>
<kwd lng="pt"><![CDATA[PM10]]></kwd>
<kwd lng="pt"><![CDATA[regressão não paramétrica]]></kwd>
<kwd lng="pt"><![CDATA[suavização kernel]]></kwd>
<kwd lng="pt"><![CDATA[suavização spline]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[  ]]></body><back>
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