{"id":2318,"date":"2023-08-03T13:42:41","date_gmt":"2023-08-03T16:42:41","guid":{"rendered":"https:\/\/www.ufrgs.br\/ppge\/?p=2318"},"modified":"2023-08-04T08:46:59","modified_gmt":"2023-08-04T11:46:59","slug":"seminario-de-pesquisa-10-08-2023-quinta-feira","status":"publish","type":"post","link":"https:\/\/www.ufrgs.br\/ppge\/seminario-de-pesquisa-10-08-2023-quinta-feira\/","title":{"rendered":"Semin\u00e1rio de Pesquisa 10\/08\/2023 &#8211; QUINTA-FEIRA"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Ocorrer\u00e1 no dia\u00a0<strong>10\/08\/2023, Quinta-Feira, \u00e0s 11h<\/strong>\u00a0na sala\u00a0<strong>401A-FCE<\/strong>\u00a0o Semin\u00e1rio de Pesquisa \u201c<strong>Global variable selection for quantile regression<\/strong>\u201d na \u00e1rea de Economia Aplicada pelo\u00a0<strong>Prof\u00ba\u00a0Eduardo Horta (PPGE\/UFRGS)<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Autores:<\/strong>&nbsp;Eduardo Horta(UFRGS), Gabriela Bettella Cybis (UFRGS) e Ta\u00eds Loureiro Bellini (UFRGS)<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Abstract<\/strong>: Quantile regression provides a parsimonious model for the conditional quantile function of the response variable \ud835\udc4c given the vector of covariates \ud835\udc4b, and describes the whole conditional distribution of the response, yielding estimators that are more robust to the presence of outliers. Quantile regression models specify, for each quantile level \ud835\udf0f, the functional form for the conditional \ud835\udf0f-th quantile of the response, which brings complexity to perform variable selection using regularization techniques, such as LASSO or adaptive LASSO (adaLASSO), as we might obtain a different set of selected variables for each quantile level. In this work, we propose a method for global variable selection and coefficient estimation in the linear quantile regression framework, imposing little restrictions on the functional form of \ud835\udefd(\u22c5), and applying group adaLASSO penalization for variable selection. We set up a Monte Carlo study comparing six different proposed estimators based on LASSO, adaLASSO and group LASSO in six scenarios that diversify sample and quantile levels grid sizes. The findings demonstrate that the selection of the tuning parameter \ud835\udf06 for penalization is critical for model selection and coefficient estimation. It was observed that the methods using traditional LASSO are more prone to include the true model as compared to adaLASSO, but renouncing model shrinkage and not removing irrelevant covariates, while the grouped approches are more effective in zeroing coefficients that are less relevant.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Ocorrer\u00e1 no dia\u00a010\/08\/2023, Quinta-Feira, \u00e0s 11h\u00a0na sala\u00a0401A-FCE\u00a0o Semin\u00e1rio de Pesquisa \u201cGlobal variable selection for quantile regression\u201d na \u00e1rea de Economia Aplicada pelo\u00a0Prof\u00ba\u00a0Eduardo Horta (PPGE\/UFRGS). Autores:&nbsp;Eduardo Horta(UFRGS), Gabriela Bettella Cybis (UFRGS) e Ta\u00eds Loureiro Bellini (UFRGS) Abstract: Quantile regression provides a parsimonious model for the conditional quantile function of the response variable \ud835\udc4c given the vector [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[9,3],"tags":[],"class_list":["post-2318","post","type-post","status-publish","format-standard","hentry","category-economia-aplicada","category-seminarios"],"_links":{"self":[{"href":"https:\/\/www.ufrgs.br\/ppge\/wp-json\/wp\/v2\/posts\/2318","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ufrgs.br\/ppge\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ufrgs.br\/ppge\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ufrgs.br\/ppge\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ufrgs.br\/ppge\/wp-json\/wp\/v2\/comments?post=2318"}],"version-history":[{"count":2,"href":"https:\/\/www.ufrgs.br\/ppge\/wp-json\/wp\/v2\/posts\/2318\/revisions"}],"predecessor-version":[{"id":2347,"href":"https:\/\/www.ufrgs.br\/ppge\/wp-json\/wp\/v2\/posts\/2318\/revisions\/2347"}],"wp:attachment":[{"href":"https:\/\/www.ufrgs.br\/ppge\/wp-json\/wp\/v2\/media?parent=2318"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ufrgs.br\/ppge\/wp-json\/wp\/v2\/categories?post=2318"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ufrgs.br\/ppge\/wp-json\/wp\/v2\/tags?post=2318"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}