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<font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Prezados,</font></font></font></p>
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<br>
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<p style="margin-bottom:0cm;line-height:100%">
<font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Bom
dia. Tenho o prazer de anunciar (abaixo) o próximo seminário do
ciclo de palestras do programa de Pós-Graduação em Estatística do
IMECC-Unicamp.</font></font></font></p>
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<br>
</p>
<p style="margin-bottom:0cm;line-height:100%">
<font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Todos
estão convidados.</font></font></font></p>
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<font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Cordialmente,</font></font></font></p>
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<br>
</p>
<p style="margin-bottom:0cm;line-height:100%">
<font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Caio
Azevedo</font></font></font></p>
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<p style="margin-bottom:0cm;line-height:100%">
<font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Title:
A robust regression method based on exponential-type kernel functions</font></font></font></p>
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<p style="margin-bottom:0cm;line-height:100%">
<font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Palestrante:
Prof. Dr. Eufrásio de Andrade Lima Neto, Departamento de
Estatística, UFPB</font></font></font><br>
<br>
<font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Data:
25/08/2017, </font></font></font><font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">14h00
sala </font></font></font><font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">121</font></font></font><font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">,
IMECC-Unicamp</font></font></font><br>
<br>
<font color="#000000"><font face="Times New Roman"><font style="font-size:14pt">Abstract:
The use of robust regression methods is common in practical
situations due to the presence of outliers. This work proposes a
robust regression method that re-weighted the outliers observations
considering type-exponential kernel functions. The convergence of the
parameter estimate algorithm is guaranteed with a low computational
cost. A comparative study between the proposed regression method
(ETKRR) against some classical robust approaches and the OLS method
is considered. We have considered synthetic datasets with X-axis
outliers, Y-axis outliers and leverage points, in a Monte Carlo
simulation framework with different sample sizes and percentage of
outliers. The results have demonstrated that the ETKRR approach
presented a competitive (or best) performance in simulation scenarios
that are similar to those found in real problems. Applications to
real datasets has showed the usefulness of the proposed method.</font></font></font></p>
<p style="margin-bottom:0cm;line-height:100%">
<br>
</p><div><br></div>-- <br><div class="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div><br></div><div>===================================================</div><div>Assistant Professor,</div><div>Department of Statistics, Institute of Mathematics,</div><div>Statistics and Scientific Computing,</div><div>University of Campinas, Brazil.</div><div><br></div><div>Office Phone : 55 - 19 - 35216060</div><div>Fax : 55 - 19 - 3521-6094</div><div><br></div><div>home-page : <a href="http://www.ime.unicamp.br/~cnaber/" target="_blank">http://www.ime.unicamp.br/~cnaber/</a></div><div>===================================================</div><div><br></div><div><div style="font-size:12.8px">"<span style="color:rgb(0,19,32);font-family:Trebuchet,Arial,Helvetica,sans-serif;font-size:14px;line-height:20px;text-align:justify;background-color:rgb(253,254,255)">Pois desde a criação do mundo os atributos invisíveis de Deus, seu eterno poder e sua natureza divina, têm sido observados claramente, podendo ser compreendidos por intermédio de tudo o que foi criado, de maneira que tais pessoas são indesculpáveis.</span><span style="color:rgb(0,19,32);font-family:Trebuchet,Arial,Helvetica,sans-serif;font-size:14px;line-height:20px;text-align:justify;background-color:rgb(253,254,255)"> </span><span style="font-size:12.8px">"</span></div><div style="font-size:12.8px"><span style="font-size:12.8px">Romanos 1:20</span></div></div></div></div></div></div></div>
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