{"id":954,"date":"2015-10-13T15:45:58","date_gmt":"2015-10-13T13:45:58","guid":{"rendered":"https:\/\/cio.umh.es\/?p=954"},"modified":"2015-10-13T15:45:58","modified_gmt":"2015-10-13T13:45:58","slug":"conferencia-del-prof-dr-d-david-guillen-conesa","status":"publish","type":"post","link":"https:\/\/cio.umh.es\/en\/2015\/10\/13\/conferencia-del-prof-dr-d-david-guillen-conesa\/","title":{"rendered":"Conferencia del Prof. Dr. D. David  Conesa Guill\u00e9n"},"content":{"rendered":"<p><!--:es--><strong>T\u00edtulo: <\/strong>Modelizaci\u00f3n espacio-temporal aplicada: Revisiting Bayesian hierarchical models, a tool to approach many highly complicated real systems<br \/>\n<b>P<\/b><strong>onente: <\/strong>David  Conesa Guill\u00e9n<br \/>\n<strong>Date:<\/strong> 20\/10\/2015 12:00 h<br \/>\n<strong>Lugar:<\/strong> Sala de Seminarios, Edificio Torretamarit<br \/>\n<strong>Resumen:<\/strong><br \/>\nEn esta charla revisaremos una de las herramientas m\u00e1s importantes del An\u00e1lisis Bayesiano, los Modelos Jer\u00e1rquicos Bayesianos. Este tipo de modelos se han hecho muy populares cuando se tiene que hacer frente a ciertas situaciones reales, como los que aparecen en \u00f3mica, en Epidemiolog\u00eda, donde puede ser normal tener decenas o cientos de miles de variables a analizar. Los Modelos Jer\u00e1rquicos Bayesianos se han utilizado de forma frecuente, pero se hacen necesarios cuando existen ciertas situaciones complejas, debido a su capacidad para tratar dichas situaciones. As\u00ed mismo, mostraremos algunos de los enfoques num\u00e9ricos (los m\u00e9todos de simulaci\u00f3n como MCMC, o aproximaciones de Laplace, como INLA), y, finalmente, presentaremos algunos ejemplos de aplicaciones con diversos ajustes pr\u00e1cticos.<br \/>\n<strong>Breve Bio:<\/strong><br \/>\nDavid Conesa Guill\u00e9n es Profesor Titular del  departamento de Estad\u00edstica e Investigaci\u00f3n Operativa en la Universitat de Val\u00e8ncia. Ha publicado numerosos art\u00edculos sobre modelizaci\u00f3n Bayesiana, es editor de las dos revistas espa\u00f1olas de estad\u00edstica: SORT y TEST. Actualmente ostenta el cargo de Presidente de la Sociedad Espa\u00f1ola de Biometr\u00eda. Ha impartido cursos sobre esta tem\u00e1tica tanto en universidades  nacionales como extranjeras.<br \/>\n<!--:--><!--:en--><strong>Title<\/strong>: Spatio-temporal modelling applied: Revisiting Bayesian hierarchical models, a tool to approach many highly complicated real systems<br \/>\n<strong>Speaker<\/strong>: David  Conesa Guill\u00e9n<br \/>\n<strong>Date<\/strong>: 20\/10\/2015 12:00h<br \/>\n<strong>Location<\/strong>: Sala de Seminarios, Edificio Torretamarit<br \/>\n<strong>Abstract<\/strong><br \/>\nIn this talk, we will review one of the most important tools of Bayesian analysis, namely the Bayesian hierarchical models. This kind of models are becoming so popular when one has to deal with many real situations such as those appearing in the omics fields, Epidemiology, where it can be natural to have tens or hundreds of thousands of variables to be analysed. Bayesian hierarchical models have been used largely but now they have become kind of necessary in all those practical complex situations because of their ability to deal with them. After reviewing the models, we will show some of the numerical approaches that have been introduced to deal with them (simulation methods such as MCMC, or Laplace approximations, such as INLA), and finally some examples of their applications in various practical settings will be presented.<br \/>\n<strong>Brief Bio:<\/strong><br \/>\nDavid  Conesa Guill\u00e9n is Associate Professor at Department of Statistics and Operations Research at the University of Valencia. He has published numerous articles on Bayesian modelling, he has taught courses on this subject both domestic and foreign universities and is editor of the two Journal of Statistics in Spain: SORT and TEST. Currently, he holds the position of President of the Spanish Region of the International Biometric Society.<!--:--><\/p>","protected":false},"excerpt":{"rendered":"<p>T\u00edtulo: Modelizaci\u00f3n espacio-temporal aplicada: Revisiting Bayesian hierarchical models, a tool to approach many highly complicated real systems<br \/>\nPonente: David  Conesa Guill\u00e9n<br \/>\nFecha: 20\/10\/2015 12:00 h<br \/>\nLugar: Sala de Seminarios, Edificio Torretamarit<br \/>\nResumen:<br \/>\nEn esta charla revisaremos una de las herramientas m\u00e1s importantes del An\u00e1lisis Bayesiano, los Modelos Jer\u00e1rquicos Bayesianos. Este tipo de modelos se han hecho muy populares cuando [&#8230;]<\/p>","protected":false},"author":3477,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_links_to":"","_links_to_target":""},"categories":[4,873],"tags":[],"_links":{"self":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/posts\/954"}],"collection":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/users\/3477"}],"replies":[{"embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/comments?post=954"}],"version-history":[{"count":0,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/posts\/954\/revisions"}],"wp:attachment":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/media?parent=954"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/categories?post=954"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/tags?post=954"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}