{"id":19054,"date":"2018-03-09T09:07:54","date_gmt":"2018-03-09T09:07:54","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/reduccion-de-dimension-en-regresion-loga%c2%adstica-funcional\/"},"modified":"2018-03-09T09:07:54","modified_gmt":"2018-03-09T09:07:54","slug":"reduccion-de-dimension-en-regresion-loga%c2%adstica-funcional","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/matematicas\/reduccion-de-dimension-en-regresion-loga%c2%adstica-funcional\/","title":{"rendered":"Reducci\u00f3n de dimensi\u00f3n en regresi\u00f3n log\u00edstica funcional"},"content":{"rendered":"<h2>Tesis doctoral de <strong> Manuel Escabias Machuca <\/strong><\/h2>\n<p>En multitud de disciplinas cient\u00edficas resulta de especial relevancia conocer la probabilidad de ocurrencia de determinados sucesos o m\u00e1s concretamente predecir una variable respuesta dicot\u00f3mica en funci\u00f3n de la informaci\u00f3n que proporcionan un conjunto de variables relacionadas con ella. La t\u00e9cnica estad\u00edstica m\u00e1s utilizada para este objetivo es el modelo de regresi\u00f3n log\u00edstica, cuyo desarrollo sigue proporcionando hoy d\u00eda resultados notables.  un problema al que es muy sensible el modelo de regresi\u00f3n log\u00edstica es el de la multicolinealidad o alta dependencia existente entre las covariables del modelo, que hace que no se pueda encontrar soluci\u00f3n apropiada a la estimaci\u00f3n de los par\u00e1metros del mismo. Otro problema que se presenta est\u00e1 en la necesidad de explicar la variable dependiente del modelo con el menor n\u00famero de regresores posible. Para la resoluci\u00f3n de estos dos problemas se proponen la utilizaci\u00f3n de un n\u00famero reducido de componentes principales que permiten una estimaci\u00f3n adecuada de los par\u00e1metros del modelo log\u00edstico en presencia de multicolinealidad.  en los \u00faltimos a\u00f1os se han desarrollado numerosas t\u00e9cnicas conducentes a modelizar variables que evolucionan en el tiempo. El desarrollo de los procesos estoc\u00e1sticos ha permitido la generalizaci\u00f3n de t\u00e9cnicas multivariantes a este campo como son el caso del an\u00e1lisis en componentes principales funcional (acpf) y del modelo de regresi\u00f3n lineal funcional para predecir una variable respuesta es dicot\u00f3mica el modelo lineal no es adecuado para explicar este hecho por lo que se introduce el modelo de regresi\u00f3n log\u00edstica funcional. se proponen adem\u00e1s diversas formas de estimaci\u00f3n aproximada, as\u00ed como soluciones a los distintos problemas que surgen basadas en componentes principales funcional.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Reducci\u00f3n de dimensi\u00f3n en regresi\u00f3n log\u00edstica funcional<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Reducci\u00f3n de dimensi\u00f3n en regresi\u00f3n log\u00edstica funcional <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Manuel Escabias Machuca <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Granada<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 20\/09\/2002<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Ana Mar\u00eda Aguilera Del Pino<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: ram\u00f3n Guti\u00e9rrez Jaimez <\/li>\n<li>Juan Romo urroz (vocal)<\/li>\n<li>jordi Oca\u00f1a rebull (vocal)<\/li>\n<li>Juan  Carlos Ru\u00edz molina (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Manuel Escabias Machuca En multitud de disciplinas cient\u00edficas resulta de especial relevancia conocer la probabilidad de ocurrencia [&hellip;]<\/p>\n","protected":false},"author":1,"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":"","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":"","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":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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