Partial least squares regression and related dimension reduction methods / R. Dennis Cook and Liliana Forzani.
| Author/creator | Cook, R. Dennis |
| Other author | Forzani, Liliana. |
| Format | Electronic |
| Edition | First edition. |
| Publication Info | Boca Raton, FL : CRC Press, 2024. |
| Description | 1 online resource |
| Supplemental Content | Full text available from eBooks on EBSCOhost |
| Subjects |
| Abstract | "Partial least squares (PLS) regression is, at its historical core, a black-box algorithmic method for dimension reduction and prediction based on an underlying linear relationship between a possibly vector-valued response and a number of predictors. Through envelopes, much more has been learned about PLS regression, resulting in a mass of information that allows an envelope bridge that takes PLS regression from a black-box algorithm to a core statistical paradigm based on objective function optimization and, more generally, connects the applied sciences and statistics in the context of PLS. This book focuses on developing this bridge. It also covers uses of PLS outside of linear regression, including discriminant analysis, non-linear regression, generalized linear models and dimension reduction generally"-- Provided by publisher. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Source of description | Description based on print version record and CIP data provided by publisher. |
| Issued in other form | Print version: Cook, R. Dennis. Partial least squares regression First edition. Boca Raton, FL : CRC Press, 2024 9781032773186 |
| Genre/form | Electronic books. |
| LCCN | 2024000158 |
| ISBN | 9781040051337 (epub) |
| ISBN | 9781003482475 (ebook) |
| ISBN | (hardback) |
| ISBN | (paperback) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |