{"id":2984,"date":"2018-09-18T13:05:42","date_gmt":"2018-09-18T17:05:42","guid":{"rendered":"https:\/\/www.med.unc.edu\/bigs2\/?page_id=2984"},"modified":"2020-10-13T18:15:39","modified_gmt":"2020-10-13T22:15:39","slug":"genv","status":"publish","type":"page","link":"https:\/\/www.med.unc.edu\/bigs2\/genv\/","title":{"rendered":"GENV: Groupwise Envelope Model"},"content":{"rendered":"<div id=\"content1\">\n<div id=\"main\">\n<div id=\"right\">\n<div id=\"right_text\">\n<div class=\"box\" style=\"text-align: left\">This is a package for fitting the groupwise envelope model. Main function genv fits the groupwise envelope model to the responses and predictors, using the maximum likelihood estimation. Function genvasy provides the asymptotic standard error matrix for estimators. We can find the dimension of the envelope subspase from u_genv. The prediction error for a given dimension is obtained from cv_genv.<\/div>\n<div class=\"box\">\n<p><strong><a href=\"https:\/\/github.com\/BIG-S2\/GENV\" target=\"new\" rel=\"noopener noreferrer\">Download<\/a><\/strong><\/p>\n<p><strong>Citation<\/strong>: Park Y, Su Z, Zhu H. Groupwise envelope models for imaging genetic analysis. <em>Biometrics<\/em>. 2017.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><!-- footer ends--><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>This is a package for fitting the groupwise envelope model. Main function genv fits the groupwise envelope model to the responses and predictors, using the maximum likelihood estimation. Function genvasy provides the asymptotic standard error matrix for estimators. We can find the dimension of the envelope subspase from u_genv. The prediction error for a given &hellip; <a href=\"https:\/\/www.med.unc.edu\/bigs2\/genv\/\" aria-label=\"Read more about GENV: Groupwise Envelope Model\">Read more<\/a><\/p>\n","protected":false},"author":1503,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-2984","page","type-page","status-publish","hentry","odd"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>GENV: Groupwise Envelope Model - BIG-S2<\/title>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"GENV: Groupwise Envelope Model - BIG-S2\" \/>\n<meta property=\"og:description\" content=\"This is a package for fitting the groupwise envelope model. Main function genv fits the groupwise envelope model to the responses and predictors, using the maximum likelihood estimation. Function genvasy provides the asymptotic standard error matrix for estimators. We can find the dimension of the envelope subspase from u_genv. The prediction error for a given &hellip; Read more\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.med.unc.edu\/bigs2\/genv\/\" \/>\n<meta property=\"og:site_name\" content=\"BIG-S2\" \/>\n<meta property=\"article:modified_time\" content=\"2020-10-13T22:15:39+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.med.unc.edu\/bigs2\/genv\/\",\"url\":\"https:\/\/www.med.unc.edu\/bigs2\/genv\/\",\"name\":\"GENV: Groupwise Envelope Model - BIG-S2\",\"isPartOf\":{\"@id\":\"https:\/\/www.med.unc.edu\/bigs2\/#website\"},\"datePublished\":\"2018-09-18T17:05:42+00:00\",\"dateModified\":\"2020-10-13T22:15:39+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/www.med.unc.edu\/bigs2\/genv\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.med.unc.edu\/bigs2\/genv\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.med.unc.edu\/bigs2\/genv\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.med.unc.edu\/bigs2\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"GENV: Groupwise Envelope Model\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.med.unc.edu\/bigs2\/#website\",\"url\":\"https:\/\/www.med.unc.edu\/bigs2\/\",\"name\":\"BIG-S2\",\"description\":\"Biostatistics and Imaging Genomics analysis lab - Statistics &amp; Signal\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.med.unc.edu\/bigs2\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"GENV: Groupwise Envelope Model - BIG-S2","robots":{"index":"noindex","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"og_locale":"en_US","og_type":"article","og_title":"GENV: Groupwise Envelope Model - BIG-S2","og_description":"This is a package for fitting the groupwise envelope model. Main function genv fits the groupwise envelope model to the responses and predictors, using the maximum likelihood estimation. Function genvasy provides the asymptotic standard error matrix for estimators. We can find the dimension of the envelope subspase from u_genv. The prediction error for a given &hellip; Read more","og_url":"https:\/\/www.med.unc.edu\/bigs2\/genv\/","og_site_name":"BIG-S2","article_modified_time":"2020-10-13T22:15:39+00:00","twitter_card":"summary_large_image","schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/www.med.unc.edu\/bigs2\/genv\/","url":"https:\/\/www.med.unc.edu\/bigs2\/genv\/","name":"GENV: Groupwise Envelope Model - BIG-S2","isPartOf":{"@id":"https:\/\/www.med.unc.edu\/bigs2\/#website"},"datePublished":"2018-09-18T17:05:42+00:00","dateModified":"2020-10-13T22:15:39+00:00","breadcrumb":{"@id":"https:\/\/www.med.unc.edu\/bigs2\/genv\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.med.unc.edu\/bigs2\/genv\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/www.med.unc.edu\/bigs2\/genv\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.med.unc.edu\/bigs2\/"},{"@type":"ListItem","position":2,"name":"GENV: Groupwise Envelope Model"}]},{"@type":"WebSite","@id":"https:\/\/www.med.unc.edu\/bigs2\/#website","url":"https:\/\/www.med.unc.edu\/bigs2\/","name":"BIG-S2","description":"Biostatistics and Imaging Genomics analysis lab - Statistics &amp; Signal","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.med.unc.edu\/bigs2\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"}]}},"_links_to":[],"_links_to_target":[],"_links":{"self":[{"href":"https:\/\/www.med.unc.edu\/bigs2\/wp-json\/wp\/v2\/pages\/2984","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.med.unc.edu\/bigs2\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.med.unc.edu\/bigs2\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.med.unc.edu\/bigs2\/wp-json\/wp\/v2\/users\/1503"}],"replies":[{"embeddable":true,"href":"https:\/\/www.med.unc.edu\/bigs2\/wp-json\/wp\/v2\/comments?post=2984"}],"version-history":[{"count":0,"href":"https:\/\/www.med.unc.edu\/bigs2\/wp-json\/wp\/v2\/pages\/2984\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.med.unc.edu\/bigs2\/wp-json\/wp\/v2\/media?parent=2984"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}