<div dir="ltr"><table border="0" cellspacing="0" cellpadding="0" align="left" width="100%" style="font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;width:1616px;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;margin-left:4.8pt;margin-right:4.8pt"><tbody><tr><td width="100%" style="width:1616px;padding:0cm"><table border="0" cellspacing="0" cellpadding="0" align="left" width="100%" style="width:1616px;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;margin-left:4.8pt;margin-right:4.8pt"><tbody><tr><td width="100%" colspan="3" style="width:1616px;padding:0cm">Caros redistas,<br><br>Gostaria de convidar a todos para o seminário do Professor (agora emérito!) Dani Gamerman na série de seminários da Escola de Matemática Aplicada da FGV, na quarta-feira que vem, 18/03 às 16h. <br><br>Cordialmente,<br><br>Luiz</td></tr></tbody></table></td></tr></tbody></table><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr"><br></div><br><br>





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<b><span style="font-size:13.0pt;font-family:"Arial",sans-serif;color:#1f497d">MODELLING EXCEEDANCES IN EXTREME VALUE THEORY<u></u><u></u></span></b></p>
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<span style="font-size:10.5pt;line-height:115%;font-family:"Arial",sans-serif;color:#595959">Extreme value theory (EVT) is the branch of Statistics concerned with extremes or tails of a distribution. It has a long list of areas of application, including Finance
 and Environmental Sciences. One of the main concerns of EVT is to model exceedances, or values beyond a sufficiently high quantile. Nice theoretical results suggest the way forward to approximate exceedance behaviour, but do not define how extreme one needs
 to be for the approximation to work well. Ad-hoc procedures are commonly used to address this issue but they suffer from the pitfalls inherent to such procedures and do not take into account the uncertainty associated. Thus, resulting inference is likely to
 be biased and/or to underestimate uncertainty. We propose a procedure that avoids such pitfalls by letting the data drive the decision of when the approximation can be safely applied, while accounting for the uncertainty of this choice. The procedures are
 extended to: 1) accommodate for the inclusion of external sources of information; 2) the time series context to incorporate temporal dependence; 3) identify the extremal behavior, and; 4) handle multivariate contexts.<u></u><u></u></span></p>
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^{<span style="font-size:10.5pt;line-height:115%;font-family:"Arial",sans-serif;color:#595959">Texto informado pelo autor.</span>}^{<span style="color:#1f497d"><u></u><u></u></span>}</p>
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<b><span style="font-family:"Arial",sans-serif;color:#1f4e79">Quando:</span></b><span style="font-family:"Arial",sans-serif"><u></u><u></u></span></p>
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<span style="font-size:10.5pt;line-height:115%;font-family:"Arial",sans-serif;color:#595959">18 de Março de 2021, às
<b>16h</b></span><span style="font-family:"Arial",sans-serif;color:#595959"><u></u><u></u></span></p>
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<span style="font-size:10.5pt;line-height:115%;font-family:"Arial",sans-serif;color:#595959">Via Zoom</span><span style="font-family:"Arial",sans-serif;color:#595959"><u></u><u></u></span></p>
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<span style="font-size:10.5pt;line-height:115%;font-family:"Arial",sans-serif;color:#595959">Registre-se com antecedência para este seminário:
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<a href="https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Ffgv-br.zoom.us%2Fmeeting%2Fregister%2FtJcsceyupjIjHtK9BmjGS2MH7CpndEK6GGZc&data=04%7C01%7Celisangela.souza%40fgv.br%7C2b8e592d95b54e14682908d8e3c346a2%7C79f6b639ab1242808077bdbeef869b33%7C0%7C0%7C637509775136792117%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=bfPsfvxnrGl2K%2BvZ0VhM2DPP1bJvXSzm%2FpFy4futld8%3D&reserved=0" target="_blank">https://fgv-br.zoom.us/meeting/register/tJcsceyupjIjHtK9BmjGS2MH7CpndEK6GGZc</a><u></u><u></u></p>
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<span style="font-size:10.5pt;line-height:115%;font-family:"Arial",sans-serif;color:#595959">Após o registro, você receberá um e-mail de confirmação contendo informações sobre conexão no seminário.</span><span style="font-family:"Arial",sans-serif"><u></u><u></u></span></p>
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<b><span style="font-size:12.0pt;line-height:115%;font-family:"Arial",sans-serif;color:#1f4e79">Palestrante:</span></b><b><span style="font-size:12.0pt;line-height:115%;font-family:"Arial",sans-serif"><u></u><u></u></span></b></p>
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<b><span style="font-size:10.5pt;line-height:115%;font-family:"Arial",sans-serif;color:#595959">Dani Gamerman</span></b><span style="font-size:10.5pt;line-height:115%;font-family:"Arial",sans-serif;color:#595959"> é Professor Titular Visitante da UFMG desde
 2019. Professor Titular (1996 a 2019) e Emérito (2021) da UFRJ. É autor dos livros Monte Carlo Markov Chain: Stochastic Simulation for Bayesian Inference (Chapman & Hall, 2006, 2a. edição) e Statistical Inference: an Integrated Approach, com Helio S. Migon
 e Francisco Louzada (Chapman & Hall, 2014, 2a. edição), além de livros nacionais.  Publicou artigos em vários periódicos de Estatística como Journal of the Royal Statistical Society Series B, Biometrika, Applied Statistics, Statistics & Computing e Journal
 of Multivariate Analysis. Tem suas atividades de pesquisas em modelos dinâmicos, estatística espacial, análise de sobrevivência, teoria de valores extremos, TRI, simulação estocástica e inferência Bayesiana.</span><span style="font-size:10.5pt;line-height:115%;font-family:"Arial",sans-serif;color:#232333"><br clear="all">
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</div><br clear="all"><div><br></div>-- <br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div dir="ltr" style="color:rgb(80,0,80)"><div dir="ltr">Luiz Max Fagundes de Carvalho</div><div dir="ltr">Lecturer, School of Applied Mathematics (EMAp), Getúlio Vargas Foundation (FGV), Brazil.</div><div dir="ltr">Praia de Botafogo, 190, Sala 511, Rio de Janeiro, RJ 22250-900.</div><div dir="ltr">Brazil</div></div></div></div></div></div></div>