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<p style="margin:0cm;font-family:Aptos;font-size:12pt" align="center"><span style="font-family:Verdana,sans-serif;font-size:11pt"><b>Title:</b> Regression Modeling of Censored Data based on Compound Scale Mixtures of Normal Distributions</span></p>
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<p style="margin:0cm;font-family:Calibri,sans-serif;font-size:11pt"><span style="font-family:Verdana,sans-serif"><b>Palestrante:</b>
</span><span style="font-family:Verdana,sans-serif;color:rgb(5,99,193)"><u><a style="color:rgb(5,99,193);margin-top:0px;margin-bottom:0px" href="https://ufjf-br.academia.edu/CAMILABORELLIZELLER" id="m_980688225524122932OWA07e08430-40bc-9888-a28a-e8edccd07d1b" target="_blank">Camila
Borelli Zeller</a></u></span></p>
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<p style="margin:0cm;font-family:Calibri,sans-serif;font-size:11pt"><span style="font-family:Verdana,sans-serif"><b>Universidade:
</b> </span><span style="font-family:Verdana,sans-serif;color:rgb(5,99,193)"><u><a style="color:rgb(5,99,193);margin-top:0px;margin-bottom:0px" href="https://www2.ufjf.br/ufjf/" id="m_980688225524122932OWA9e7e8a92-a613-f1f4-b1f1-67c203bced1f" target="_blank">UFJF</a></u></span></p>
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<span style="font-family:Verdana,sans-serif"><b> </b></span></p>
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<span style="font-family:Verdana,sans-serif;font-size:11pt;line-height:115%"><b>Abstract:</b> In the framework of censored regression models, the distribution of the error term can depart significantly from normality, for instance, due to the presence
of multimodality, skewness and/or atypical observations. In this paper we propose a novel censored linear regression model where the random errors follow a finite mixture of scale mixtures of normal (SMN) distribution. The SMN is an attractive class of symmetrical
heavy-tailed densities that includes the normal, Student-t, slash and the contaminated normal distribution as special cases. This approach allows us to model data with great flexibility, accommodating simultaneously multimodality, heavy tails and skewness
depending on the structure of the mixture components. We develop an analytically tractable and efficient EM-type algorithm for iteratively computing the maximum likelihood estimates of the parameters, with standard errors and prediction of the censored values
as a by-products. The proposed algorithm has closed-form expressions at the E-step, that rely on formulas for the mean and variance of the truncated SMN distributions. The efficacy of the method is verified through the analysis of simulated and real datasets.
The methodology addressed in this paper is implemented in the R package CensMixReg.</span></p>
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<span style="font-family:Verdana,sans-serif">October 3, 2024</span></p>
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<span style="font-family:Verdana,sans-serif">12pm, São Paulo, Brasil (UTC/GMT -03:00)</span></p>
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<span style="font-family:Verdana,sans-serif">Via Zoom</span></p>
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<p style="margin:0cm;font-family:Calibri,sans-serif;font-size:11pt">Rua Quatá, 300 - Vila Olímpia - São Paulo/SP - Brasil - CEP: 04546-042 | Tel: (11) 4504-2400</p>
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</div></div><br clear="all"><div><br></div><span class="gmail_signature_prefix">-- </span><br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small">Hedibert Freitas Lopes, PhD</span><br style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small">Professor of Statistics and Econometrics</span><br style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small">INSPER - Institute of Education and Research</span><br style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small">Rua Quatá, 300 - São Paulo, SP 04546-042 Brazil</span><br style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small">Phone: +55 11 4504-2343</span><br style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><span style="color:rgb(0,0,0);font-family:Calibri,Arial,Helvetica,sans-serif,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols;font-size:small"><a href="http://www.hedibert.org" target="_blank">www.hedibert.org</a></span><br></div></div></div>