{"id":368,"date":"2019-05-15T11:17:10","date_gmt":"2019-05-15T10:17:10","guid":{"rendered":"http:\/\/blogs.kent.ac.uk\/pgrseminars\/?p=368"},"modified":"2019-05-15T11:17:13","modified_gmt":"2019-05-15T10:17:13","slug":"17-may-jie-lie-stats","status":"publish","type":"post","link":"https:\/\/blogs.kent.ac.uk\/pgrseminars\/2019\/05\/15\/17-may-jie-lie-stats\/","title":{"rendered":"17 May ~ Jie Lie (Stats)"},"content":{"rendered":"<p><strong><span style=\"font-family: 'Calibri',sans-serif;color: black\">Title: <\/span><\/strong><span style=\"font-family: 'Calibri',sans-serif;color: black\">Covariance regression analysis<\/span><\/p>\n<p><span style=\"font-family: 'Calibri',sans-serif;color: black\">\u00a0<\/span><\/p>\n<p><strong><span style=\"font-family: 'Calibri',sans-serif;color: black\">Abstract:\u00a0<\/span><\/strong><span style=\"font-family: 'Calibri',sans-serif;color: black\">\u200bI will introduce covariance regression analysis which is proposed recently. This method mainly takes the auxiliary information matrix as the covariates. Then for a p-dimensional response vector, the covariance matrix is modeled by the linear combination of the auxiliary information matrix. I will share the basic ideas of the covariance regression model, furthermore, three types of estimators: maximum likelihood, ordinary least squares, and feasible generalized least squares estimators will be introduced. Finally, an example will illustrate the comparison of these three types of estimators.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Title: Covariance regression analysis \u00a0 Abstract:\u00a0\u200bI will introduce covariance regression analysis which is proposed recently. This method mainly takes the auxiliary information matrix as the &hellip; <a href=\"https:\/\/blogs.kent.ac.uk\/pgrseminars\/2019\/05\/15\/17-may-jie-lie-stats\/\">Read&nbsp;more<\/a><\/p>\n","protected":false},"author":57430,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[170526,1],"tags":[],"_links":{"self":[{"href":"https:\/\/blogs.kent.ac.uk\/pgrseminars\/wp-json\/wp\/v2\/posts\/368"}],"collection":[{"href":"https:\/\/blogs.kent.ac.uk\/pgrseminars\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.kent.ac.uk\/pgrseminars\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.kent.ac.uk\/pgrseminars\/wp-json\/wp\/v2\/users\/57430"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.kent.ac.uk\/pgrseminars\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":1,"href":"https:\/\/blogs.kent.ac.uk\/pgrseminars\/wp-json\/wp\/v2\/posts\/368\/revisions"}],"predecessor-version":[{"id":369,"href":"https:\/\/blogs.kent.ac.uk\/pgrseminars\/wp-json\/wp\/v2\/posts\/368\/revisions\/369"}],"wp:attachment":[{"href":"https:\/\/blogs.kent.ac.uk\/pgrseminars\/wp-json\/wp\/v2\/media?parent=368"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.kent.ac.uk\/pgrseminars\/wp-json\/wp\/v2\/categories?post=368"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.kent.ac.uk\/pgrseminars\/wp-json\/wp\/v2\/tags?post=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}