| 期刊全稱 | Applied Matrix and Tensor Variate Data Analysis | | 影響因子2023 | Toshio Sakata | | 視頻video | http://file.papertrans.cn/160/159949/159949.mp4 | | 發(fā)行地址 | Reviews applications of matrix and tensor variate data analysis by world-leading researchers in several representative applied fields including, psychology, audio signals, image data and genetics.Trea | | 學(xué)科分類 | SpringerBriefs in Statistics | | 圖書封面 |  | | 影響因子 | This book provides comprehensive reviews of recent progress in matrix variate and tensor variate data analysis from applied points of view. Matrix and tensor approaches for data analysis are known to be extremely useful for recently emerging complex and high-dimensional data in various applied fields. The reviews contained herein cover recent applications of these methods in psychology (Chap. 1), audio signals (Chap. 2) , image analysis? from tensor principal component analysis (Chap. 3), and image analysis from decomposition (Chap. 4), and genetic data (Chap. 5) . Readers will be able to understand the present status of these techniques as applicable to their own fields. ?In Chapter 5 especially, a theory of tensor normal distributions, which is a basic in statistical inference, is developed, and multi-way regression, classification, clustering, and principal component analysis are exemplified under tensor normal distributions. Chapter 6 treats one-sided tests under matrix variate andtensor variate normal distributions, whose theory under multivariate normal distributions has been a popular topic in statistics since the books of Barlow et al. (1972) and Robertson et al. (1988). Ch | | Pindex | Book 2016 |
The information of publication is updating
|
|
|Archiver|手機(jī)版|小黑屋|
派博傳思國際
( 京公網(wǎng)安備110108008328)
GMT+8, 2025-10-6 06:05
發(fā)表于 2025-3-21 17:56:58
