| Title: |
A variant of sparse partial least squares for variable selection and data exploration |
| Authors: |
Yaffe, Kristine; Hunt, MJO; Weissfeld, L; Boudreau, RM; Aizenstein, H; Newman, AB; Simonsick, EM; Van, DR; Thomas, F; Rosano, C |
| Publisher Information: |
eScholarship, University of California |
| Publication Year: |
2014 |
| Collection: |
University of California: eScholarship |
| Description: |
When data are sparse and/or predictors multicollinear, current implementation of sparse partial least squares (SPLS) does not give estimates for non-selected predictors nor provide a measure of inference. In response, an approach termed "all-possible" SPLS |
| Document Type: |
article in journal/newspaper |
| Language: |
unknown |
| Relation: |
qt3xp6432b; https://escholarship.org/uc/item/3xp6432b |
| Availability: |
https://escholarship.org/uc/item/3xp6432b |
| Rights: |
public |
| Accession Number: |
edsbas.C4D88CEC |
| Database: |
BASE |