{"id":71,"date":"2014-10-22T21:16:13","date_gmt":"2014-10-23T02:16:13","guid":{"rendered":"http:\/\/blog.espol.edu.ec\/asofcnm\/?p=71"},"modified":"2014-10-22T21:24:21","modified_gmt":"2014-10-23T02:24:21","slug":"box-jenkins-time-series-analysis","status":"publish","type":"post","link":"https:\/\/blog.espol.edu.ec\/asofcnm\/2014\/10\/22\/box-jenkins-time-series-analysis\/","title":{"rendered":"Box-Jenkins Time Series  Analysis"},"content":{"rendered":"<p>Contenido:<\/p>\n<p>Introduction<br \/>\n\u2022 Defining an ARIMA model<br \/>\n\u2022 Building an ARIMA model<br \/>\nExamples<br \/>\nUnivariate ARIMA Models<br \/>\n2T.l AruMA model identification<br \/>\n2T.2 Estimating parameters and diagnostic checking<br \/>\n2T.3 Forecasting<br \/>\n2T.4 Identifying and replacing (estimating) missing values<br \/>\nIntervention Analysis<br \/>\n2T.5 Constructing a preintervention model<br \/>\n2T.6 Identifying the form of the intervention and estimating<br \/>\nintervention parameters<br \/>\n2T.7 Modeling several interventions<br \/>\nMultiple-Input Transfer Function Models<br \/>\n2T.8 Identifying the transfer function<br \/>\n2T.9 Specifying the transfer function<br \/>\n2T.I0 Modeling the output series<br \/>\n2T.ll Diagnostic checking<br \/>\n2T.12 Forecasting the predictor series<br \/>\n2T.13 Calculating psiweights and forecasting the output series<\/p>\n<p style=\"text-align: center\"><a href=\"https:\/\/www.dropbox.com\/s\/883plm9g2rmnfcg\/box-jenkins.pdf?dl=0\" target=\"_blank\">Descargar<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Contenido: Introduction \u2022 Defining an ARIMA model \u2022 Building an ARIMA model Examples Univariate ARIMA Models 2T.l AruMA model identification 2T.2 Estimating parameters and diagnostic checking 2T.3 Forecasting 2T.4 Identifying and replacing (estimating) missing values Intervention Analysis 2T.5 Constructing a preintervention model 2T.6 Identifying the form of the intervention and estimating intervention parameters 2T.7 Modeling [&hellip;]<\/p>\n","protected":false},"author":9132,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1216452],"tags":[1216453,1216455,14351,1216479],"class_list":["post-71","post","type-post","status-publish","format-standard","hentry","category-prediccion-y-pronosticos","tag-ing","tag-ingenieria-en-estadistica-informatica","tag-logistica-y-transporte","tag-prediccion-y-pronosticos"],"_links":{"self":[{"href":"https:\/\/blog.espol.edu.ec\/asofcnm\/wp-json\/wp\/v2\/posts\/71","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.espol.edu.ec\/asofcnm\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.espol.edu.ec\/asofcnm\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.espol.edu.ec\/asofcnm\/wp-json\/wp\/v2\/users\/9132"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.espol.edu.ec\/asofcnm\/wp-json\/wp\/v2\/comments?post=71"}],"version-history":[{"count":2,"href":"https:\/\/blog.espol.edu.ec\/asofcnm\/wp-json\/wp\/v2\/posts\/71\/revisions"}],"predecessor-version":[{"id":73,"href":"https:\/\/blog.espol.edu.ec\/asofcnm\/wp-json\/wp\/v2\/posts\/71\/revisions\/73"}],"wp:attachment":[{"href":"https:\/\/blog.espol.edu.ec\/asofcnm\/wp-json\/wp\/v2\/media?parent=71"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.espol.edu.ec\/asofcnm\/wp-json\/wp\/v2\/categories?post=71"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.espol.edu.ec\/asofcnm\/wp-json\/wp\/v2\/tags?post=71"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}