{"id":2118,"date":"2024-12-06T11:00:52","date_gmt":"2024-12-06T03:00:52","guid":{"rendered":"https:\/\/changjinyuan.com\/?p=2118"},"modified":"2025-07-09T16:33:07","modified_gmt":"2025-07-09T08:33:07","slug":"%e7%b3%bb%e5%88%97%e4%bb%a3%e8%a1%a8%e6%80%a7%e5%b7%a5%e4%bd%9c%e4%b8%80%ef%bc%9a%e8%b6%85%e9%ab%98%e7%bb%b4%e5%8d%8f%e5%8f%98%e9%87%8f%e7%ad%9b%e9%80%89%e4%b8%8e%e6%95%b0%e6%8d%ae%e9%99%8d%e7%bb%b4","status":"publish","type":"post","link":"https:\/\/changjinyuan.com\/index.php\/publications\/publications-proxy\/2118\/","title":{"rendered":"\u7cfb\u5217\u4ee3\u8868\u6027\u5de5\u4f5c\u4e00\uff1a\u8d85\u9ad8\u7ef4\u534f\u53d8\u91cf\u7b5b\u9009\u4e0e\u6570\u636e\u964d\u7ef4\u7684\u7cfb\u5217\u65b0\u65b9\u6cd5"},"content":{"rendered":"<ul>\n<li><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/changjinyuan.com\/wp-content\/uploads\/2025\/07\/On-the-Modeling-and-Prediction-of-High-Dimensional-Functional-Time-Series.pdf\"><strong>Chang, J.<\/strong>, Fang, Q., Qiao, X., &amp; Yao, Q. (2024+). On the modeling and prediction of high-dimensional functional time series. <strong><em>Journal of the American Statistical Association<\/em><\/strong>, in press.<\/a><\/span><\/li>\n<li><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/changjinyuan.com\/wp-content\/uploads\/2024\/12\/Modelling-matrix-time-series-via-a-tensor-CP-decomposition.pdf\"><strong>Chang, J.<\/strong>, <strong>He, J.<\/strong>, <strong>Yang, L.<\/strong>, &amp; Yao, Q. (2023). Modelling matrix time series via a tensor CP-decomposition. <em><strong>Journal of the Royal Statistical Society: Series B<\/strong><\/em>, 85, 127-148.<\/a><\/span><\/li>\n<li><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/changjinyuan.com\/wp-content\/uploads\/2024\/12\/Principal-component-analysis-for-second-order-stationary-vector-time-series.pdf\"><strong>Chang, J.<\/strong>, Guo, B., &amp; Yao, Q. (2018). Principal component analysis for second-order stationary vector time series. <em><strong>The Annals of Statistics<\/strong><\/em>, 46, 2094-2124.<\/a><\/span><\/li>\n<li><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/changjinyuan.com\/wp-content\/uploads\/2024\/12\/Local-independence-feature-screening-for-nonparametric-and-semiparametric-models-by-marginal-empirical-likelihood.pdf\"><strong>Chang, J.<\/strong>, Tang, C. Y., &amp; Wu, Y. (2016). Local independence feature screening for nonparametric and semiparametric models by marginal empirical likelihood. <em><strong>The Annals of Statistics<\/strong><\/em>,\u00a0 44, 515-539.<\/a><\/span><\/li>\n<li><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/changjinyuan.com\/wp-content\/uploads\/2024\/12\/High-dimensional-stochastic-regression-with-latent-factors-endogeneity-and-nonlinearity.pdf\"><strong>Chang, J.<\/strong>, Guo, B., &amp; Yao, Q. (2015). High dimensional stochastic regression with latent factors, endogeneity and nonlinearity. <em><strong>Journal of Econometrics<\/strong><\/em>, 189,\u00a0 297-312.<\/a><\/span><\/li>\n<li><span style=\"color: #000000;\"><a style=\"color: #000000;\" href=\"https:\/\/changjinyuan.com\/wp-content\/uploads\/2024\/12\/Marginal-empirical-likelihood-and-sure-independence-feature-screening.pdf\"><strong>Chang, J.<\/strong>, Tang, C. Y., &amp; Wu, Y. (2013). Marginal empirical likelihood and sure independence feature screening. <em><strong>The Annals of Statistics<\/strong><\/em>, 41, 2123-2148.<\/a><\/span><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>\u8fd9\u4e00\u7c7b\u522b\u7684\u7814\u7a76\u5173\u6ce8\u9ad8\u7ef4\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u7684\u6a21\u578b\u6784\u5efa\u3001\u9884\u6d4b\u4ee5\u53ca\u7edf\u8ba1\u7279\u6027\u5206\u6790\uff0c\u4e3b\u8981\u89e3\u51b3\u5728\u9ad8\u7ef4\u590d\u6742\u52a8\u6001\u6570\u636e\u4e2d\u7684\u7279\u5f81\u63d0\u53d6\u4e0e\u7ed3\u6784\u5316\u5904\u7406\u95ee\u9898\u3002<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[17],"tags":[],"class_list":["post-2118","post","type-post","status-publish","format-standard","hentry","category-publications-proxy"],"acf":[],"lang":"cn","translations":{"cn":2118,"en":2124},"pll_sync_post":[],"_links":{"self":[{"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/posts\/2118","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/comments?post=2118"}],"version-history":[{"count":18,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/posts\/2118\/revisions"}],"predecessor-version":[{"id":5111,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/posts\/2118\/revisions\/5111"}],"wp:attachment":[{"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/media?parent=2118"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/categories?post=2118"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/tags?post=2118"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}