| 書(shū)目名稱 | Multivariate Reduced-Rank Regression | | 副標(biāo)題 | Theory, Methods and | | 編輯 | Gregory C. Reinsel,Raja P. Velu,Kun Chen | | 視頻video | http://file.papertrans.cn/642/641325/641325.mp4 | | 概述 | Offers techniques that are particularly relevant for the analysis of large dimensional data sets.Provides guidance in offering elegant, simplified interpretations of data, as well as developing models | | 叢書(shū)名稱 | Lecture Notes in Statistics | | 圖書(shū)封面 |  | | 描述 | .This book provides an account of multivariate reduced-rank regression, a tool of multivariate analysis that enjoys a broad array of applications. In addition to a historical review of the topic, its connection to other widely used statistical methods, such as multivariate analysis of variance (MANOVA), discriminant analysis, principal components, canonical correlation analysis, and errors-in-variables models, is also discussed...This new edition incorporates Big Data methodology and its applications, as well as high-dimensional reduced-rank regression, generalized reduced-rank regression with complex data, and sparse and low-rank regression methods. Each chapter contains developments of basic theoretical results, as well as details on computational procedures, illustrated with numerical examples drawn from disciplines such as biochemistry, genetics, marketing, and finance. ..This book is designed for advanced students, practitioners, and researchers, who may deal withmoderate and high-dimensional multivariate data. Because regression is one of the most popular statistical methods, the multivariate regression analysis tools described should provide a natural way of looking at large | | 出版日期 | Book 2022Latest edition | | 關(guān)鍵詞 | high-dimensional reduced-rank regression; generalized reduced-rank regression; non-Gaussian; mixed data | | 版次 | 2 | | doi | https://doi.org/10.1007/978-1-0716-2793-8 | | isbn_softcover | 978-1-0716-2791-4 | | isbn_ebook | 978-1-0716-2793-8Series ISSN 0930-0325 Series E-ISSN 2197-7186 | | issn_series | 0930-0325 | | copyright | Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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