书目名称 | Reduced Rank Regression |
副标题 | With Applications to |
编辑 | Heinz Schmidli |
视频video | |
丛书名称 | Contributions to Statistics |
图书封面 |  |
描述 | Reduced rank regression is widely used in statistics to model multivariate data. In this monograph, theoretical and data analytical approaches are developed for the application of reduced rank regression in multivariate prediction problems. For the first time, both classical and Bayesian inference is discussed, using recently proposed procedures such as the ECM-algorithm and the Gibbs sampler. All methods are motivated and illustrated by examples taken from the area of quantitative structure-activity relationships (QSAR). |
出版日期 | Book 1995 |
关键词 | Covariance matrix; Latent variable model; Likelihood; Multivariate Verfahren; Regression Analysis; Regres |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-642-50015-2 |
isbn_softcover | 978-3-7908-0871-1 |
isbn_ebook | 978-3-642-50015-2Series ISSN 1431-1968 Series E-ISSN 2628-8966 |
issn_series | 1431-1968 |
copyright | Springer-Verlag Berlin Heidelberg 1995 |