<html><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><p class="">Caros</p><p class="">O PPGEst UFRGS tem o prazer de divulgar o seminário do professor Giuseppe
Cavaliere (University of Bologna) no dia 27 de outubro (sexta-feira). O
seminário será presencial. Seguem os dados do seminário</p><p class=""><br class=""></p><p class=""><strong class="">Título:</strong> Bootstrap inference in the presence of bias</p><p class=""><br class=""><strong class="">Resumo:</strong> We consider bootstrap inference for
estimators which are (asymptotically) biased. We show that, even when
the bias term cannot be consistently estimated, valid inference can be
obtained by proper implementations of the bootstrap. Specifically, we
show that the prepivoting approach of Beran (1987, 1988), originally
proposed to deliver higher-order refinements, restores bootstrap
validity by transforming the original bootstrap p-value into an
asymptotically uniform random variable. We propose two different
implementations of prepivoting (plug-in and double bootstrap), and
provide general high-level conditions that imply validity of bootstrap
inference. To illustrate the practical relevance and implementation of
our results, we discuss five examples: (i) inference on a target
parameter based on model averaging; (ii) ridge-type regularized
estimators; (iii) nonparametric regression; (iv) a location model for
infinite variance data; and (v) dynamic panel data models.</p><p class=""><br class=""><strong class="">Link do artigo:</strong> <a href="https://arxiv.org/abs/2208.02028" target="_blank" rel="noreferrer" class="">https://arxiv.org/abs/2208.02028</a></p><p class=""><br class=""><strong class="">Palestrante:</strong> Giuseppe Cavaliere (University of Bologna)</p><div class=""><b class="">Mediador: </b>Flávio Ziegelmann</div><p class=""><br class=""><strong class="">Data:</strong> 27 de Outubro de 2023 (sexta-feira)<br class=""><strong class="">Horário:</strong> 13h30min <br class=""><strong class="">Local:</strong> Sala A101 do Instituto de Matemática e Estatística da UFRGS (Av. Bento Gonçalves, 9500 Prédio 43-111)</p>
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<div class="">Muito obrigada</div>
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<div class="">Gabriela Cybis</div></body></html>