.png){kind=icon}
.png){kind=icon}
Return
Sparse partial robust M regression
.png){kind=icon}
OA
AI
DOI：10.1016/j.chemolab.2015.09.019.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Sparse partial robust M regression is introduced as a new regression method. It is the first dimension reduction and regression algorithm that yields estimates with a partial least squares like interpretability that are sparse and robust with respect to both vertical outliers and leverage points. A simulation study underpins these claims. Real data examples illustrate the validity of the approach. (C) 2015 Elsevier B.V. All rights reserved.
Keywords:
Biplot
Partial least squares
Robustness
Sparse estimation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.8
Papers:
4.6K
Citations:
1.2W
View more organizations