{"id":5480,"date":"2023-01-09T14:59:46","date_gmt":"2023-01-09T17:59:46","guid":{"rendered":"https:\/\/www.est.ufmg.br\/portal\/?page_id=5480"},"modified":"2024-07-25T10:40:11","modified_gmt":"2024-07-25T13:40:11","slug":"mestrado-estrutura-curricular","status":"publish","type":"page","link":"https:\/\/www.est.ufmg.br\/portal\/mestrado-estrutura-curricular\/","title":{"rendered":"P\u00f3s Gradua\u00e7\u00e3o &#8211; Mestrado &#8211; Estrutura Curricular"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"5480\" class=\"elementor elementor-5480\" data-elementor-post-type=\"page\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-0ff5d7e elementor-section-full_width elementor-section-height-default elementor-section-height-default\" data-id=\"0ff5d7e\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-401be2d\" data-id=\"401be2d\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-891e960 elementor-widget elementor-widget-shortcode\" data-id=\"891e960\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">\t\t<div data-elementor-type=\"section\" data-elementor-id=\"5309\" class=\"elementor elementor-5309\" data-elementor-post-type=\"elementor_library\">\n\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4196f936 elementor-section-full_width elementor-section-height-default elementor-section-height-default\" data-id=\"4196f936\" data-element_type=\"section\" data-e-type=\"section\" id=\"menu-atuariais\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t\t<div class=\"elementor-background-overlay\"><\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-38946e94\" data-id=\"38946e94\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1c9328fd elementor-widget elementor-widget-heading\" data-id=\"1c9328fd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Mestrado<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-7c2abc6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7c2abc6\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;sticky&quot;:&quot;top&quot;,&quot;sticky_on&quot;:[&quot;desktop&quot;,&quot;tablet&quot;,&quot;mobile&quot;],&quot;sticky_offset&quot;:0,&quot;sticky_effects_offset&quot;:0,&quot;sticky_anchor_link_offset&quot;:0}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-72d1d89\" data-id=\"72d1d89\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-dcc935b elementor-icon-list--layout-inline elementor-align-center elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"dcc935b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items elementor-inline-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.est.ufmg.br\/portal\/\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-home\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Home DEST<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.est.ufmg.br\/portal\/pos-graduacao\/\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-home\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Home P\u00f3s-gradua\u00e7\u00e3o<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.est.ufmg.br\/portal\/mestrado-est\/\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chart-area\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Mestrado<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.est.ufmg.br\/portal\/mestrado-est\/#informacoes-m\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-home\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Informa\u00e7\u00f5es<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.est.ufmg.br\/portal\/mestrado-alunos-egressos\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-check\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Alunos Egressos<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.est.ufmg.br\/portal\/mestrado-alunos-matriculados\/\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-check\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Alunos Matriculados<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.est.ufmg.br\/portal\/pos-graduacao-processo-seletivo\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"far fa-check-circle\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Processo Seletivo<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.est.ufmg.br\/portal\/mestrado-estrutura-curricular\/#estrutura-curricular-mes\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-check-circle\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Estrutura Curricular<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.est.ufmg.br\/portal\/mestrado-provas-gabaritos\/\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"far fa-check-circle\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Provas Anteriores e Gabaritos<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.est.ufmg.br\/portal\/mestrado-estrutura-curricular\/#ementas-mestrado\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-check-circle\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Ementas<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-inline-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.est.ufmg.br\/portal\/mestrado-dissertacao-mestrado\/\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-clipboard\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Disserta\u00e7\u00f5es Defendidas<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-a7d3ec3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a7d3ec3\" data-element_type=\"section\" data-e-type=\"section\" id=\"estrutura-curricular-mes\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8c990d5\" data-id=\"8c990d5\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-39c6750 elementor-widget elementor-widget-heading\" data-id=\"39c6750\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Estrutura Curricular<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6957906 elementor-widget elementor-widget-text-editor\" data-id=\"6957906\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>O Programa de Mestrado em Estat\u00edstica da UFMG \u00e9 composto por disciplinas semestrais obrigat\u00f3rias e optativas com as seguintes distribui\u00e7\u00f5es por per\u00edodo e suas respectivas ementas (informa\u00e7\u00f5es adicionais sobre algumas disciplinas podem ser encontradas nas homepages dos professores).<\/p><p><span style=\"color: #000080;\"><strong>1\u00ba Semestre Letivo<\/strong><\/span><\/p><table style=\"height: 150px;\" border=\"1\" width=\"500\" cellpadding=\"0\"><tbody><tr><td><strong>Disciplina<\/strong><\/td><td><strong>Classifica\u00e7\u00e3o<\/strong><\/td><td><strong>Carga Hor\u00e1ria<\/strong><\/td><td><strong>No\u00a0de Cr\u00e9ditos<\/strong><\/td><\/tr><tr><td>Probabilidade<\/td><td>Obrigat\u00f3ria<\/td><td>60 horas-aula<\/td><td>4<\/td><\/tr><tr><td>Infer\u00eancia Estat\u00edstica<\/td><td>Obrigat\u00f3ria<\/td><td>60 horas-aula<\/td><td>4<\/td><\/tr><tr><td>Semin\u00e1rios 1A<\/td><td>Obrigat\u00f3ria<\/td><td>15 horas-aula<\/td><td>1<\/td><\/tr><\/tbody><\/table><p><strong>Obs.:\u00a0<\/strong>Disciplina Semin\u00e1rios 1A: a nota est\u00e1 associada \u00e0 presen\u00e7a do aluno nos semin\u00e1rios do Departamento de Estat\u00edstica realizados ao longo do semestre<\/p><p><span style=\"color: #000080;\"><strong>2\u00ba Semestre Letivo<\/strong><\/span><\/p><p><strong>Obs.:\u00a0<\/strong>At\u00e9 final de agosto deve ser preenchida, no colegiado, a ficha com defini\u00e7\u00e3o do nome do orientador e co-orientador (se houver).<\/p><table style=\"height: 150px;\" border=\"1\" width=\"500\" cellpadding=\"0\"><tbody><tr><td><strong>Disciplina<\/strong><\/td><td><strong>Classifica\u00e7\u00e3o<\/strong><\/td><td><strong>Carga Hor\u00e1ria<\/strong><\/td><td><strong>N\u00ba de Cr\u00e9ditos<\/strong><\/td><\/tr><tr><td>Optativa 1<\/td><td>Optativa<\/td><td>60 horas-aula<\/td><td>4<\/td><\/tr><tr><td>Optativa 2<\/td><td>Optativa<\/td><td>60 horas-aula<\/td><td>4<\/td><\/tr><tr><td>Semin\u00e1rios 1B<\/td><td>Obrigat\u00f3ria<\/td><td>15 horas-aula<\/td><td>1<\/td><\/tr><\/tbody><\/table><p><strong>Obs.:\u00a0<\/strong>Disciplina Semin\u00e1rios 1B: 50% da nota est\u00e1 associada \u00e0 presen\u00e7a do aluno nos semin\u00e1rios do Departamento de Estat\u00edstica. Os outros 50 pontos ser\u00e3o assim divididos: 25 pontos dados pelo orientador e os outros 25 pontos correspondem \u00e0 avalia\u00e7\u00e3o da apresenta\u00e7\u00e3o de um projeto que o aluno far\u00e1 ao fim do semestre. A nota da apresenta\u00e7\u00e3o ser\u00e1 a m\u00e9dia das notas dadas por uma banca definida pelo colegiado.<\/p><p><span style=\"color: #000080;\"><strong>3\u00ba Semestre Letivo<\/strong><\/span><\/p><table style=\"height: 150px;\" border=\"1\" width=\"500\" cellpadding=\"0\"><tbody><tr><td><strong>Disciplina<\/strong><\/td><td><strong>Classifica\u00e7\u00e3o<\/strong><\/td><td><strong>Carga Hor\u00e1ria<\/strong><\/td><td><strong>No\u00a0de Cr\u00e9ditos<\/strong><\/td><\/tr><tr><td>Semin\u00e1rios de Estat\u00edstica II<\/td><td>Obrigat\u00f3ria<\/td><td>30 horas-aula<\/td><td>2<\/td><\/tr><tr><td>Optativa 3<\/td><td>Optativa<\/td><td>60 horas-aula<\/td><td>4<\/td><\/tr><tr><td>Est\u00e1gio doc\u00eancia<\/td><td>\u00a0<\/td><td>\u00a0<\/td><td>\u00a0<\/td><\/tr><\/tbody><\/table><p><strong>Obs.:\u00a0<\/strong>A disciplina Semin\u00e1rios II consiste na prepara\u00e7\u00e3o da Qualifica\u00e7\u00e3o, cuja defesa deve ser feita at\u00e9 o final do semestre (julho).\u00a0<strong>A data da defesa do exame de qualifica\u00e7\u00e3o deve ser marcada 30 dias antes na secretaria do colegiado.<\/strong><\/p><p><span style=\"color: #000080;\"><strong>4\u00ba Semestre Letivo<\/strong><\/span><\/p><table style=\"height: 88px;\" border=\"1\" width=\"1172\" cellpadding=\"0\"><tbody><tr><td><strong>Disciplina<\/strong><\/td><td><strong>Classifica\u00e7\u00e3o<\/strong><\/td><td><strong>Carga Hor\u00e1ria<\/strong><\/td><td><strong>N\u00ba de Cr\u00e9ditos<\/strong><\/td><\/tr><tr><td>Elabora\u00e7\u00e3o de disserta\u00e7\u00e3o<\/td><td>Obrigat\u00f3ria<\/td><td>&#8211;<\/td><td>&#8211;<\/td><\/tr><\/tbody><\/table><table style=\"height: 44px;\" border=\"1\" width=\"1317\" cellpadding=\"0\"><tbody><tr><td><strong>Obs.:\u00a0<\/strong>Para alunos bolsistas, o prazo da CAPES para a defesa da disserta\u00e7\u00e3o \u00e9 de 2 anos, portanto a mesma deve ser feita at\u00e9 mar\u00e7o. Para os alunos n\u00e3o-bolsistas, o prazo da CAPES \u00e9 de 2 anos e meio, portanto a defesa deve ser feita at\u00e9 setembro.<\/td><\/tr><\/tbody><\/table><p><strong>Disciplina isolada:<\/strong>\u00a0Todos os programas de P\u00f3s-Gradua\u00e7\u00e3o da UFMG oferecem a op\u00e7\u00e3o da disciplina ser cursada por um aluno que n\u00e3o seja regularmente matriculado (disciplina isolada). Assim, qualquer pessoa pode se inscrever, mas naturalmente o pedido \u00e9 julgado por um colegiado e est\u00e1 sujeito \u00e0 avalia\u00e7\u00e3o das condi\u00e7\u00f5es do candidato acompanhar a disciplina e tamb\u00e9m da disponibilidade de vagas. O mais recomendado no\u00a0 programa \u00e9 come\u00e7ar no primeiro semestre, mas de qualquer forma qualquer pessoa interessada pode se inscrever em disciplinas do segundo semestre. Maiores informa\u00e7\u00f5es, inclusive sobre datas de inscri\u00e7\u00e3o, podem ser obtidas na secretaria do Programa de P\u00f3s-gradua\u00e7\u00e3o.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-e55a92d elementor-section-full_width elementor-section-height-default elementor-section-height-default\" data-id=\"e55a92d\" data-element_type=\"section\" data-e-type=\"section\" id=\"ementas-mestrado\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-2fba262\" data-id=\"2fba262\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-11bdc63 elementor-widget elementor-widget-heading\" data-id=\"11bdc63\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Ementas Disciplinas<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b058c3e elementor-widget elementor-widget-text-editor\" data-id=\"b058c3e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: center;\"><strong><u>DISCIPLINAS OBRIGAT\u00d3RIAS<\/u><\/strong><\/p><p><strong> <u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u><\/strong><strong style=\"font-style: inherit; background-color: var( --e-global-color-5d17d6b );\">Probabilidade<\/strong><\/p><p><strong>Ementa<\/strong>: Experimento aleat\u00f3rio, espa\u00e7o de probabilidade, eventos, probabilidade condicional. Vari\u00e1vel aleat\u00f3ria, esperan\u00e7a, vari\u00e2ncia, momentos, distribui\u00e7\u00e3o conjunta. Principais distribui\u00e7\u00f5es de probabilidade. Fun\u00e7\u00f5es geradoras de momentos e caracter\u00edsticas. Leis Fraca e Forte dos grandes n\u00fameros e Teorema Central do Limite.<\/p><p>Bibliografia<\/p><p>James, B.R. Probabilidade: Um curso em n\u00edvel intermedi\u00e1rio. Projeto Euclides, Rio de Janeiro, 1981.<\/p><p>Ross, S.A. First course in probability. 5 ed., Prentice Hall, N. Jersey, 1988.<\/p><p><strong>\u00a0<\/strong><\/p><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>Infer\u00eancia Estat\u00edstica<\/strong><\/p><p><strong>Ementa<\/strong>: Amostra aleat\u00f3ria. Distribui\u00e7\u00f5es amostrais. Estima\u00e7\u00e3o pontual e por intervalo. Sufici\u00eancia. Completude e Fam\u00edlias exponenciais. M\u00e9todos dos momentos. Estimadores n\u00e3o viciados e de m\u00ednima vari\u00e2ncia. Estimadores de m\u00e1xima verossimilhan\u00e7a. Algoritmo EM. Estimadores invariantes. Estimadores de Bayes. Testes de hip\u00f3teses. Teoria de Neyman-Pearson. Testes uniformemente mais poderosos. Teste de raz\u00e3o de verossimilhan\u00e7a. Propriedades assint\u00f3ticas. Tabelas de conting\u00eancia. Introdu\u00e7\u00e3o \u00e0 infer\u00eancia n\u00e3o-param\u00e9trica. Bootstrap e Jackknife.\u00a0<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>Azzalini, A. Statistical Inference Based on the Likelihood. London:Chapman and Hall, 1996.<\/li><li>Bickel, P.J., Doksum, K.A. Mathematical statistics: basic ideas and selected topics, S\u00e3o Francisco: Holden Day, 1977.<\/li><li>Fergunson, T.S. Mathematical statistics. New York: Academic Press. 1967.<\/li><li>Hogg, R.V., Craig, A.T. Introduction to mathematical statistics, Macmillan, London, 1978.<\/li><li>Garthwaite, P.H., Jolliffe, I.T., Jones, B. Statistical Inference New York: Prentice Hall, 1995.\u00a0<\/li><li>Lehmann, E.L. Theory of Point Estimation. New York: John Wiley Sons, Wiley Series in Probability and Mathematical Statistics, 1983.<\/li><li>Casella, G., Berger, R. L. (2002) Statistical Inference, 2 nd Edition, Duxbury.<\/li><li>Mood, A., Graybill, F., Boes, D. (1974) Introduction to the theory of statistics. MacGraw Hill (ISBN 0-07-042864-6).<\/li><\/ul><p style=\"text-align: center;\"><span style=\"text-decoration: underline;\"><strong>DISCIPLINAS OPTATIVAS<\/strong><\/span><\/p><ul><li>An\u00e1lise de Dados Longitudinais<\/li><li>An\u00e1lise Real<\/li><li>An\u00e1lise de S\u00e9ries Temporais<\/li><li>An\u00e1lise de Sobreviv\u00eancia<\/li><li>Estat\u00edstica Bayesiana I<\/li><li>Estat\u00edstica Bayesiana II<\/li><li>Estat\u00edstica Computacional<\/li><li>Estat\u00edstica Espacial<\/li><li>Infer\u00eancia Avan\u00e7ada<\/li><li>Modelos Lineares Generalizados<\/li><li>Probabilidade Avan\u00e7ada<\/li><li>Processos Estoc\u00e1sticos<\/li><li>T\u00f3picos Especiais em Estat\u00edstica<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>An\u00e1lise de Dados Longitudinais<\/strong><\/p><p><strong>Ementa<\/strong>: Introdu\u00e7\u00e3o \u00e0 Dados Longitudinais &#8211; Exemplos. Desenhos de Estudos Longitudinais. T\u00e9cnicas Tradicionais: Perspectiva Hist\u00f3rica. An\u00e1lise Explorat\u00f3ria de Dados Longitudinais. Modelando a M\u00e9dia e a Estrutura de Covari\u00e2ncia. Infer\u00eancia Estat\u00edstica: M\u00ednimos Quadrados, M\u00e1xima Verossimilhan\u00e7a, GEE. Modelos Lineares Mistos. Modelos Lineares Generalizados para Dados Longitudinais. Modelos Marginais: Equa\u00e7\u00f5es Generalizadas de Estima\u00e7\u00e3o (GEE). Medidas Repetidas. Tratamento de Dados Perdidos.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>*Fitzmaurice, Laird e Ware (2011). Applied Longitudinal Analysis. Segunda edi\u00e7\u00e3o.<\/li><li>*Diggle, Heagerty, Liang e Zeger (2002). Analysis of Longitudinal Data. Segunda edi\u00e7\u00e3o.<\/li><li>*Verbeke e Molenberghs (2000). Linear Mixed Models for Longitudinal Data.<\/li><li>*Pinheiro e Bates (2000). Mixed-Effects Models in S and S-plus.<\/li><li>*Twisk (2003). Applied Longitudinal Data Analysis for Epidemiology.<\/li><li>*Molenberghs e Verbeke (2005). Models for Discrete Longitudinal Data.<\/li><li>*Molenberghs e Kenward (2007). Missing Data in Clinical Studies.<\/li><li>*Singer, Nobre e Rocha (2015). An\u00e1lise de Dados Longitudinias &#8211; Vers\u00e3o preliminar &#8211;\u00a0<a href=\"http:\/\/www.ime.usp.br\/~jmsinger\/MAE0610\">http:\/\/www.ime.usp.br\/~jmsinger\/MAE0610<\/a>.<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>An\u00e1lise Real<\/strong><\/p><p><strong>Ementa<\/strong>: Conjuntos e Fun\u00e7\u00f5es. Enumerabilidade. N\u00fameros Reais. Seq\u00fc\u00eancias e S\u00e9ries de N\u00fameros Reais. Topologia da Reta. Limites de Fun\u00e7\u00f5es. Fun\u00e7\u00f5es Cont\u00ednuas. Derivadas. Integral de Riemann. Seq\u00fc\u00eancias e S\u00e9ries de Fun\u00e7\u00f5es.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>Lima, E. L., Curso de An\u00e1lise Vol. 1, IMPA, Projeto Euclides, Rio de Janeiro, RJ, 2004.<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>An\u00e1lise de S\u00e9ries Temporais<\/strong><\/p><p><strong>Ementa<\/strong>: Modelos ARIMA: Condi\u00e7\u00f5es de estacionariedade e invertibilidade. Os modelos ARIMA. Identifica\u00e7\u00e3o de modelos: fun\u00e7\u00e3o de autocorrela\u00e7\u00e3o (ACF) e fun\u00e7\u00e3o de autocorrela\u00e7\u00e3o parcial (PACF). Estima\u00e7\u00e3o, verifica\u00e7\u00e3o e sele\u00e7\u00e3o de modelos. An\u00e1lise de res\u00edduos. Previs\u00e3o com modelos ARIMA. Modelos sazonais. Modelos de Espa\u00e7o de Estados: Defini\u00e7\u00e3o. Tipos de Modelos. Forma de espa\u00e7o de estados. Filtro de Kalman. Estima\u00e7\u00e3o e previs\u00e3o. Modelos de Espa\u00e7o de Estados N\u00e3o-Gaussianos. T\u00f3picos: An\u00e1lise de interven\u00e7\u00e3o. Modelos de fun\u00e7\u00e3o de transfer\u00eancia. Detec\u00e7\u00e3o e modelagem de outliers. Modelos para s\u00e9ries com longa depend\u00eancia. Modelos lineares autorregressivos m\u00e9dias m\u00f3veis generalizados.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>*Benjamin, M. A., R. A. Rigby, and D. M. Stasinopoulos (2003). Generalized autoregressive moving average models. Journal of the American Statistical Association, 98, pp. 214-223.<\/li><li>*Box, G.E.P. and Jenkins, G.M. Time Series Analysis: Forecasting and Control. San Francisco: Holden-Day, 1976<\/li><li>*Brockwell, P; J., Davis, R. A. (1991) Time Series: Theory and Methods, 2nd ed. New York: Springer Verlag<\/li><li>*Davis, R.A., Dunsmuir, W.T.M. and Streett, S.B. (2003). Observation-driven models for Poisson counts. Biometrika, 90, pp 777-790.<\/li><li>*Hamilton, J. D. (1994) Time Series Analysis, Princeton University Press, New Jersey.<\/li><li>*Harvey, A.C. (1989) Forecasting, structural time series models and the Kalman filter. Cambridge: University Press.<\/li><li>*Palma, W. (2007) Long-Memory Time Series. New Jersey: Wiley<\/li><li>*Shumway, R. H., Stoffer, D. S. (2006) Time Series Analysis and its Applications: with R examples. New York: Springer.<\/li><li>*Wei w.w.s., (1990) Time Series Analysis: Univariate and Multivariate Methods, Addison \u2013 Wesley Publishing company.<\/li><\/ul><p><strong> <u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u><\/strong><strong>An\u00e1lise de Sobreviv\u00eancia<\/strong><\/p><p><strong>Ementa<\/strong>: Conceitos B\u00e1sicos: pesquisa cient\u00edfica, tempo de falha e censura, exemplos de aplica\u00e7\u00e3o, especifica\u00e7\u00e3o do tempo de falha, estima\u00e7\u00e3o da fun\u00e7\u00e3o de sobreviv\u00eancia, compara\u00e7\u00e3o de curvas de sobreviv\u00eancia. Modelos Param\u00e9tricos: distribui\u00e7\u00f5es exponencial, Weibull e lognormal, m\u00e9todo de m\u00e1xima verossimilhan\u00e7a, modelos de tempo de vida acelerada, verificando a adequa\u00e7\u00e3o de modelos, exemplos. Modelo de Regress\u00e3o de Cox: forma do modelo, o m\u00e9todo de m\u00e1xima verossimilhan\u00e7a parcial, verificando a adequa\u00e7\u00e3o do modelo, covari\u00e1veis dependente no tempo, o modelo estratificado, exemplos de aplica\u00e7\u00e3o. T\u00f3picos Especiais: censura intervalar e dados grupados, testes de degrada\u00e7\u00e3o, an\u00e1lise de sobreviv\u00eancia multivariada, riscos competitivos.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>Livro Texto: Colosimo e Giolo (2006) &#8211; An\u00e1lise de Sobreviv\u00eancia Aplicada (www.ufpr.br\/~giolo\/Livro).<\/li><li>Klein e Moeschberger (2003) &#8211; Survival Analysis.<\/li><li>Collett (2003) &#8211; Modelling Survival Data in Medical Research.<\/li><li>Hosmer e Lemeshow (1999) &#8211; Applied Survival Analysis.<\/li><li>Lawless (2011) &#8211; Statistical Models and Methods for Lifetime Data<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>Estat\u00edstica Bayesiana I<\/strong><\/p><p><strong>Ementa<\/strong>: Paradigma Bayesiano. Aleatoriedade. Probabilidade Subjetiva. Teorema de Bayes. Modelo Bayesiano: Distribui\u00e7\u00f5es a priori, a posteriori e preditiva. Princ\u00edpio da Verossimilhan\u00e7a. Compara\u00e7\u00e3o com o Paradigma cl\u00e1ssico. Distribui\u00e7\u00f5es a priori. Determina\u00e7\u00e3o da distribui\u00e7\u00e3o a priori: Fam\u00edlias conjugadas, distribui\u00e7\u00f5es de refer\u00eancia distribui\u00e7\u00f5es n\u00e3o \u2013informativas, distribui\u00e7\u00e3o vaga. Modelos hier\u00e1rquicos. Misturas finitas. Modelos Uniparam\u00e9tricos e multiparam\u00e9tricos. Infer\u00eancia para os modelos Binomial, Poisson, Geom\u00e9trico, Uniforme, Exponencial e Normal com m\u00e9dia ou vari\u00e2ncia conhecida. Modelos Normal com m\u00e9dia e vari\u00e2ncia desconhecida, Modelo multinomial. Infer\u00eancia. Elementos de teoria de Decis\u00e3o. Regras de decis\u00e3o. Fun\u00e7\u00e3o perda. Princ\u00edpio da maximiza\u00e7\u00e3o da utilidade esperada. Estima\u00e7\u00e3o Pontual. Intervalo de Credibilidade. Teste de Hip\u00f3tese: Fator de Bayes e teste de signific\u00e2ncia Bayesiano completo. Predi\u00e7\u00e3o.\u00a0 Compara\u00e7\u00e3o e valida\u00e7\u00e3o de modelos. Fator de Bayes, probabilidade a posteriori do Modelo, res\u00edduos Bayesianos, ordenadas preditivas condicionais. DIC.\u00a0 Aproxima\u00e7\u00f5es computacionais para estas medidas Modelos de regress\u00e3o e Sele\u00e7\u00e3o de vari\u00e1veis. Modelo de Regressao Linear: An\u00e1lise conjugada. Analise de refer\u00eancia (distribui\u00e7\u00f5es de Jeffreys e G-Zellner). Sele\u00e7\u00e3o de vari\u00e1veis via busca estoc\u00e1stica. Modelos Probit, Logit a log-linear. M\u00e9todos computacionais. M\u00e9todos num\u00e9ricos de integra\u00e7\u00e3o, M\u00e9todo da Rejei\u00e7\u00e3o, SIR; m\u00e9todos de simula\u00e7\u00e3o Monte Carlo via cadeias de Markov.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>Estat\u00edstica Bayesiana (2018), B. Murteira, C. D. Paulino, M. A. Amaral Turkman, G. L. Silva, 2\u00aa edi\u00e7\u00e3o.<\/li><li>Statistical Inference: An Integrated Approach (2015) H. S. Migon, D.\u00a0 Gamerman e F. Louzada, 2a. edi\u00e7\u00e3o, CRC Press.<\/li><li>Bayesian Core: A Practical Approach to Computational Bayesian Statistics (2006) C. P. Robert , J.M. Marin. Springer.<\/li><li>Markov Chain Monte Carlo: Stochastic Simulation for Bayesian\u00a0 Inference (2006), D. Gamerman, H. Lopes, 2a edi\u00e7\u00e3o, Chapman and Hall\/CRC.<\/li><li>Markov Chain Monte Carlo in Pratice. (1995), W. R. Gilks, S. Richardson, D.J. Spiegelhalter, Chapman and Hall\/CRC.<\/li><li>Kendall\u2019s Advanced Theory of Statistics, Volume 2B: Bayesian Inference (1994), Anthony O&#8217;Hagan, Edward\u00a0 Arnold, Great Britain.<\/li><li>The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation (2007), C. P. Robert, Springer.<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>Estat\u00edstica Bayesiana II<\/strong><\/p><p><strong>Ementa<\/strong>: Parte 1: Modelagem Bayesiana: Constru\u00e7\u00e3o e especifica\u00e7\u00e3o de modelos. Misturas de distribui\u00e7\u00f5es. Modelos hier\u00e1rquicos. Modelos gr\u00e1ficos. Identificabilidade de modelos. Sele\u00e7\u00e3o de modelos. Problemas. Parte 2: M\u00e9todos computacionais: Integra\u00e7\u00e3o de Monte Carlo. Rejection Sampling e Importance Sampling. MCMC: Teoria e implementa\u00e7\u00e3o (Gibbs Sampling e Metropolis-Hastings). Problemas.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>Notas de aula.<\/li><li>Robert, C. P. (2007) The Bayesian choice: from decision-theoretic foundations to computational implementation. 2ed., Springer .<\/li><li>Gamerman, D and Lopes, H. F. (2006) Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference. 2ed, Chapman &amp; Hall\/CRC.<\/li><li>Robert, C. P and Casella, G. (2004) Monte Carlo Statistical Methods. 2ed., Springer.<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>Estat\u00edstica Computacional<\/strong><\/p><p><strong>Ementa<\/strong>: Gera\u00e7\u00e3o de vari\u00e1veis aleat\u00f3rias discretas e cont\u00ednuas: Gera\u00e7\u00e3oo de n\u00fameros pseudoaleat\u00f3rios, gera\u00e7\u00e3o por transforma\u00e7\u00e3o, m\u00e9todo da transforma\u00e7\u00e3o inversa. Gera\u00e7\u00e3o de vari\u00e1veis aleat\u00f3rias Poisson e Binomial. M\u00e9todo polar para gerar vetores aleat\u00f3rios normais. Gera\u00e7\u00e3o de trajet\u00f3rias de processos de Poisson e suas extens\u00f5es. Gera\u00e7\u00e3o atrav\u00e9s de cadeias de Markov via Monte Carlo: M\u00e9todo da aceita\u00e7\u00e3o e rejei\u00e7\u00e3o, reamostragem por import\u00e2ncia, m\u00e9todo da rejei\u00e7\u00e3o adaptativa (ARS), Metropolis-Hasting, Amostrador de Gibbs. Monitoramento de converg\u00eancia. Otimiza\u00e7\u00e3o e resolu\u00e7\u00e3o de equa\u00e7\u00f5es n\u00e3o lineares: M\u00e9todo da bisse\u00e7\u00e3o, M\u00e9todo de Newton, Escore de Fisher, M\u00e9todo da secante. M\u00e9todos Newton-Like, Gauss-Newton e algoritmo Nelder-Mead. M\u00e9todos de integra\u00e7\u00e3o: Integra\u00e7\u00e3o Monte Carlo, m\u00e9todos de Newton-C\u00f4tes, quadratura de Gauss-Hermite. T\u00e9cnicas de redu\u00e7\u00e3o de vari\u00e2ncia: Amostragem por import\u00e2ncia, Amostragem Antit\u00e9tica, vari\u00e1veis de controle e Rao-Blackwelliza\u00e7\u00e3o. M\u00e9todo de Monte Carlo: Estima\u00e7\u00e3o pontual e intervalar. Testes de hip\u00f3teses. Algoritmos EM e suas vers\u00f5es: Algoritmo EM, EM condicional, EM estoc\u00e1stico, Monte Carlo EM (MCEM), EM com aproxima\u00e7\u00e3o estoc\u00e1stica (SAEM). T\u00e9cnica de aumento\u00a0 de dados. Bootstrap, Jackknife, testes de permuta\u00e7\u00e3o.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>Bradley Efron and Robert J. Tibshirani (1994). An introduction to the bootstrap. Chapman and Hall\/CRC.<\/li><li>Christian P. Robert and George Casella (2009). Introducing Monte Carlo Methods with R. Springer.<\/li><li>Geof H. Givens, Jennifer A. Hoeting (1\u00ba Edi\u00e7\u00e3o, 2005). Computational Statistics. Wiley-Interscience.<\/li><li>Maria L. Rizzo (2008). \\textit{Statistical Computing with R}. Chapman and Hall.<\/li><li>Owen Jones, Robert Maillardet, and Andrew Robinson (2009). Introduction to Scientific Programming and Simulation using r. CRC Press.<\/li><li>Sheldon M. Ross (2013). Simulation. Academic Press.<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>Estat\u00edstica Espacial<\/strong><\/p><p><strong>Ementa<\/strong>: Dados geoestat\u00edsticos (com refer\u00eancia pontual) e dados de \u00e1rea. Campos aleat\u00f3rios Markovianos. Processo Gaussiano. Estacionariedade e isotropia. Variogramas e fun\u00e7\u00f5es de covari\u00e2ncias. Kriging. Padr\u00f5es pontuais espaciais e espa\u00e7o-temporais. Modelagem hier\u00e1rquica para processos\u00a0 espaciais. Modelos espaciais n\u00e3o Gaussianos. Estrat\u00e9gias computacionais para ajusta conjuntos de dados espaciais. Modelos n\u00e3o estacion\u00e1rios. Modelos CAR e SAR. Modelos para processos espaciais multivariados. Modelos com coeficientes variando espacialmente. Modelos para processos espa\u00e7o-temporais.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>Banerjee, S., Carlin, B.P. and Gelfand, A.E. (2004) Hierarchical modeling and analysis for spatial data, Boca Raton: Chapman &amp; Hall\/CRC.<\/li><li>Bivand, R. S., Pebesma E., Rubio, V. G. (2013) Applied spatial data analysis with R, 2 ed, New York: Springer.<\/li><li>Cressie, N.A.C. (1993) Statistics for spatial data, New York: John Wiley &amp; Sons.<\/li><li>Diggle, P.J. and Ribeiro, P.J. (2007) Model-based geostatistics, New York: Springer.<\/li><li>Gelfand, A. E., Diggle, P. J., Fuentes, M. and Guttorp, P. (2010) Handbook of Spatial Statistics, Boca Raton: Chapman &amp; Hall\/CRC.<\/li><li>Gaetan, C. and Guyon, X. (2010) Spatial Statistics and Modeling. New York: Springer.<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>Infer\u00eancia Avan\u00e7ada<\/strong><\/p><p><strong>Ementa<\/strong>: Todo o conte\u00fado da disciplina \u00e9 ministrado sob a \u00f3tica de Teoria da Medida. Popula\u00e7\u00f5es, Amostras e Modelos; Estat\u00edsticas, Sufici\u00eancia e Completude; Teoria da Decis\u00e3o; Conceitos b\u00e1sicos de Infer\u00eancia Estat\u00edstica; Estima\u00e7\u00e3o n\u00e3o-viciada, UMVUE; Estima\u00e7\u00e3o em modelos param\u00e9tricos, Infer\u00eancia Bayesiana, M\u00e1xima Verossimilhan\u00e7a, Efici\u00eancia assint\u00f3tica; Estima\u00e7\u00e3o n\u00e3o-param\u00e9trica, estima\u00e7\u00e3o de densidades, equa\u00e7\u00f5es de estima\u00e7\u00e3o generalizadas, Bootstrap, Jackknife; Testes de Hip\u00f3teses, testes uniformemente mais poderosos, teste da raz\u00e3o de verossimilhan\u00e7as; Intervalos\/conjuntos de Confian\u00e7a, Constru\u00e7\u00e3o de intervalos\/conjuntos.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>Shao, J. Mathematical Statistics. Springer Texts in Statistics, 2nd edition, 2003.<\/li><li>Lehman, E. L. Theory of Point Estimation. New York: John Wiley &amp; Sons, 1983.<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>Modelos Lineares Generalizados<\/strong><\/p><p><strong>Ementa<\/strong>: Conceitos b\u00e1sicos e nota\u00e7\u00f5es. Modelos lineares. M\u00e9todo de m\u00ednimos quadrados. Testes de hip\u00f3teses e intervalos de confian\u00e7a. Fam\u00edlia exponencial de distribui\u00e7\u00e3o. Componentes dos modelos lineares generalizados. M\u00e9todo de m\u00e1xima verossimilhan\u00e7a. Estima\u00e7\u00e3o e Infer\u00eancia. Verifica\u00e7\u00e3o da adequa\u00e7\u00e3o de modelos. Modelos para respostas binomiais. Modelos para tabelas de conting\u00eancias. Modelos para contagens. Modelos para dados de sobreviv\u00eancia . Modelos multivariados.\u00a0<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>Aitkin, M., Anderson, D., Franncis, B. Hinde, J. Statistical modelling in GLIM. Oxford: Oxford University Press, 1989.\u00a0\u00a0<\/li><li>Cordeiro, G.M. Modelos lineares generalizados, X SINAPE, Rio de Janeiro, 1992.\u00a0<\/li><li>Dem\u00e9trio, C.B.G. Modelos lineares generalizados na experimenta\u00e7\u00e3o agron\u00f4mica, SEAGRO,\u00a0 Porto Alegre, 1993.<\/li><li>Dobson, A.J. An introduction to generalized linear models. London: Chapman &amp; Hall, 1989.<\/li><li>Fahmeir, L., Tutz, G. Multivariate Statistical Modelling based on generalized linear models. Springer Verlag, 1994.\u00a0<\/li><li>McCullagh, P., Nelder, J.A. Generalized linear models. 2 ed. London: Chapman &amp; Hall, 1991. Seber, G.A.F. Linear regression analysis, John Wiley, 1977.<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>Probabilidade Avan\u00e7ada<\/strong><\/p><p><strong>Ementa<\/strong>: de conjuntos, Teorema da Classe Mon\u00f3tona.\u00a0 Fun\u00e7\u00f5es mensur\u00e1veis, espa\u00e7os de Probabilidade. Medidas de probabilidade e suas fun\u00e7\u00f5es de distribui\u00e7\u00e3o. Teorema de extens\u00e3o de Carath\u00e9odory, Integra\u00e7\u00e3o.\u00a0 Propriedades da integral. Esperan\u00e7a matem\u00e1tica. Teoremas de converg\u00eancia. Espa\u00e7o produto. Independ\u00eancia. Teorema de extens\u00e3o de Kolmogorov. Esperan\u00e7a condicional. Teorema de Radon \u2013 Nikodym, Converg\u00eancia em Probabilidade e Converg\u00eancia Quase Certa. Lei Fraca dos Grandes N\u00fameros Lemas de Borel-Cantelli. Lei Forte dos Grandes N\u00fameros.Converg\u00eancia de s\u00e9ries. Teorema das tr\u00eas s\u00e9ries. Aplica\u00e7\u00f5es.Teorema Central do Limite,Fun\u00e7\u00f5es Caracter\u00edsticas\u00a0 &#8211; Propriedades. Unicidade e invers\u00e3o. Teoremas de converg\u00eancia TCL para Vari\u00e1veis Aleat\u00f3rias I.I.D.\u00a0 TCL para Arranjos Triangulares. Teorema de Lyapunov. Teorema de Lindeberg \u2013 Feller. Aplica\u00e7\u00f5es.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>Chung, K.L.(1974). A Course in Probability Theory. Second Edition, Academic Press.<\/li><li>Durrett, R.(1996). Probability: Theory and Examples. Second Edition, Duxbury Press<\/li><li>Feller, W.(1971). An Introduction to Probability Theory and its Applications. Vol. I e Vol. II, Second Edition, Wiley.<\/li><li>Kolmogorov, A. N.\u00a0 (1956) Foundations of the Theory of Probability. Transl edit. By Morrison, N. Chelsea Pub. Company.<\/li><li>Ash, Robert (1972) Real Analysis and Probability. Academic Press<\/li><li>Rudin, W.\u00a0 (1986) Real and Complex Analysis. McGraw \u2013Hill<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>Processos Estoc\u00e1sticos<\/strong>.<\/p><p>Pr\u00e9-requisitos: Probabilidade em n\u00edvel mestrado<\/p><p><strong>Ementa<\/strong>: Parte 1: Cadeias de Markov discretas, finitas e enumer\u00e1veis. Introdu\u00e7\u00e3o a cadeias finitas. Classifica\u00e7\u00e3o de estados. Tempos de retorno. Recorr\u00eancia e transi\u00eancia. Recorr\u00eancia positiva e recorr\u00eancia nula. Processos de ramifica\u00e7\u00e3o Parte 2: Cadeias de Markov e tempos de mistura. Varia\u00e7\u00e3o total e tempos de mistura. Exemplos. Acoplamento. Parte 3: Martingais Esperan\u00e7a Condicional. Martingais. Teorema amostragem opcional. Teoremas de converg\u00eancia de Martingais.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>David A. Levin, Yuval Peres, Elizabeth L. Wilmer. Markov Chains and Mixing Times. AMS, 2002.<\/li><li>Pierre Br\u00e9maud. Markov Chains: Gibbs Fields, Monte Carlo Simulation and Queues. Springer, 1999.<\/li><li>J. R. Norris. Markov Chains. Cambridge University Press, 1998.<\/li><\/ul><p><strong><u><img decoding=\"async\" class=\"size-full wp-image-4328 alignleft\" src=\"https:\/\/www.est.ufmg.br\/portal\/wp-content\/uploads\/2022\/12\/check.png\" alt=\"\" width=\"40\" height=\"34\" \/><\/u>T\u00f3picos Especiais em Estat\u00edstica<\/strong><\/p><p>Ementa: Abordagem de t\u00f3picos espec\u00edficos estat\u00edstica que n\u00e3o tenham sido contemplados por outras disciplinas e que podem variar a cada oferecimento, de acordo interesse do Colegiado do Curso.<\/p><p><strong>Bibliografia<\/strong><\/p><ul><li>Selecionada de acordo com os t\u00f3picos a serem abordados na disciplina.<\/li><\/ul><p><strong>\u00a0<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Estrutura Curricular O Programa de Mestrado em Estat\u00edstica da UFMG \u00e9 composto por disciplinas semestrais obrigat\u00f3rias e optativas com as seguintes distribui\u00e7\u00f5es por per\u00edodo e suas respectivas ementas (informa\u00e7\u00f5es adicionais sobre algumas disciplinas podem ser encontradas nas homepages dos professores). 1\u00ba Semestre Letivo Disciplina Classifica\u00e7\u00e3o Carga Hor\u00e1ria No\u00a0de Cr\u00e9ditos Probabilidade Obrigat\u00f3ria 60 horas-aula 4 Infer\u00eancia [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"no-sidebar","site-content-layout":"page-builder","ast-site-content-layout":"full-width-container","site-content-style":"unboxed","site-sidebar-style":"unboxed","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":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","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":""},"class_list":["post-5480","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.est.ufmg.br\/portal\/wp-json\/wp\/v2\/pages\/5480","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.est.ufmg.br\/portal\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.est.ufmg.br\/portal\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.est.ufmg.br\/portal\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.est.ufmg.br\/portal\/wp-json\/wp\/v2\/comments?post=5480"}],"version-history":[{"count":62,"href":"https:\/\/www.est.ufmg.br\/portal\/wp-json\/wp\/v2\/pages\/5480\/revisions"}],"predecessor-version":[{"id":14444,"href":"https:\/\/www.est.ufmg.br\/portal\/wp-json\/wp\/v2\/pages\/5480\/revisions\/14444"}],"wp:attachment":[{"href":"https:\/\/www.est.ufmg.br\/portal\/wp-json\/wp\/v2\/media?parent=5480"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}