{"id":771,"date":"2026-11-13T14:01:39","date_gmt":"2026-11-13T13:01:39","guid":{"rendered":"https:\/\/blogg.lnu.se\/disa\/?p=771"},"modified":"2026-11-13T14:01:39","modified_gmt":"2026-11-13T13:01:39","slug":"welcome-to-our-higher-research-seminar-in-november","status":"publish","type":"post","link":"https:\/\/blogg.lnu.se\/disa\/?p=771","title":{"rendered":"Welcome to our Higher Research Seminar in November"},"content":{"rendered":"\n<p><strong>When?<\/strong> November 27, 14.00-16.00<br><strong>Where? <\/strong>Online, <a href=\"https:\/\/lnu-se.zoom.us\/j\/61812638609?pwd=zy5Z2oFW3lhVh3C0bqYAqBJFpRNwnm.1&amp;from=addon\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/lnu-se.zoom.us\/j\/61812638609?pwd=zy5Z2oFW3lhVh3C0bqYAqBJFpRNwnm.1&amp;from=addon<\/a><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Abstracts<\/h2>\n\n\n\n<p><strong>Mahalanobis Distance and Angle under a SCAD-Dual Modified-Cholesky Precision Estimator: The Gaussian case <\/strong>\u2013 <em>Deliang Dai from Department of Economics and Statistics<\/em><strong><br><\/strong>We study finite-sample and asymptotic properties of Mahalanobis distances and angles computed with a row-separable modified-Cholesky precision estimator that combines SCAD selection and a positive-semidefinite quadratic penalty. For an independent Gaussian observation, we give the exact conditional generalized-chi-square distribution of the estimated squared distance, a finite-sample deviation inequality, and a central limit theorem on the $\\sqrt{2p}$ scale. For the Mahalanobis cosine between two deterministic vectors, we obtain a finite-sample perturbation bound and an asymptotic normal approximation with an explicit direction-dependent Gaussian quadratic-form variance. Separate conditions permit centering at the true cosine and feasible studentization. \u00a0The estimator is defined by two local-linear-approximation updates, whose agreement with an oracle path is established under explicit initialization, signal-separation and tuning assumptions. Simulation and empirical studies are presented to evaluate the theoretical results.\u00a0<\/p>\n\n\n\n<p><strong>Nonlinear forecasting with many predictors using mixed data sampling kernel ridge regression models <\/strong>\u2013 <em>Kristofer M\u00e5nsson from Department of Economics and Statistics<\/em><strong><br><\/strong>Policy institutes such as central banks need accurate forecasts of key measures of economic activity to design stabilization policies that reduce the severity of economic fluctuations. Therefore, this paper develops a kernel ridge regression estimator in a mixed data sampling framework. Kernel ridge regression can handle many predictors with a nonlinear relationship to the target variable. Consequently, it has potential to improve the currently used principal component-based methods when the economic data follow a nonlinear factor structure. In a Monte Carlo study, we show that the kernel ridge regression approach is superior in terms of mean square error and is more robust than principal component-based methods to different nonlinear data generating processes. By using a dataset consisting of 24 economic indicators, we forecast Swedish gross domestic production. The results confirm the superiority of the kernel ridge regression approach. Therefore, we suggest that policy institutes consider the use of kernel-based approaches when forecasting key measures of economic activity.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>When? November 27, 14.00-16.00Where? Online, https:\/\/lnu-se.zoom.us\/j\/61812638609?pwd=zy5Z2oFW3lhVh3C0bqYAqBJFpRNwnm.1&amp;from=addon Abstracts Mahalanobis Distance and Angle under a SCAD-Dual Modified-Cholesky Precision Estimator: The Gaussian case \u2013 Deliang Dai from Department of Economics and StatisticsWe study finite-sample and asymptotic properties of Mahalanobis distances and angles computed with a row-separable modified-Cholesky precision estimator that combines SCAD selection and a positive-semidefinite quadratic penalty. [&hellip;]<\/p>\n","protected":false},"author":19939,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[93],"tags":[],"class_list":["post-771","post","type-post","status-publish","format-standard","hentry","category-blogg"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\r\n<title>Welcome to our Higher Research Seminar in November - DISA<\/title>\r\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\r\n<link rel=\"canonical\" href=\"https:\/\/blogg.lnu.se\/disa\/?p=771\" \/>\r\n<meta property=\"og:locale\" content=\"en_US\" \/>\r\n<meta property=\"og:type\" content=\"article\" \/>\r\n<meta property=\"og:title\" content=\"Welcome to our Higher Research Seminar in November - DISA\" \/>\r\n<meta property=\"og:description\" content=\"When? November 27, 14.00-16.00Where? Online, https:\/\/lnu-se.zoom.us\/j\/61812638609?pwd=zy5Z2oFW3lhVh3C0bqYAqBJFpRNwnm.1&amp;from=addon Abstracts Mahalanobis Distance and Angle under a SCAD-Dual Modified-Cholesky Precision Estimator: The Gaussian case \u2013 Deliang Dai from Department of Economics and StatisticsWe study finite-sample and asymptotic properties of Mahalanobis distances and angles computed with a row-separable modified-Cholesky precision estimator that combines SCAD selection and a positive-semidefinite quadratic penalty. 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November 27, 14.00-16.00Where? Online, https:\/\/lnu-se.zoom.us\/j\/61812638609?pwd=zy5Z2oFW3lhVh3C0bqYAqBJFpRNwnm.1&amp;from=addon Abstracts Mahalanobis Distance and Angle under a SCAD-Dual Modified-Cholesky Precision Estimator: The Gaussian case \u2013 Deliang Dai from Department of Economics and StatisticsWe study finite-sample and asymptotic properties of Mahalanobis distances and angles computed with a row-separable modified-Cholesky precision estimator that combines SCAD selection and a positive-semidefinite quadratic penalty. 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