The solution path of the generalized lasso
Abstract/Contents
- Abstract
- We present a path algorithm for the generalized lasso problem. This problem penalizes the l1 norm of a matrix D times the coefficient vector, and has a wide range of applications, dictated by the choice of D. Our algorithm is based on solving the dual of the generalized lasso, which facilitates computation and conceptual understanding of the path. For D=I (the usual lasso), we draw a connection between our approach and the well-known LARS algorithm. For an arbitrary D, we derive an unbiased estimate of the degrees of freedom of the generalized lasso fit. This estimate turns out to be quite intuitive in many applications.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2011 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Tibshirani, Ryan Joseph |
|---|---|
| Associated with | Stanford University, Department of Statistics |
| Primary advisor | Taylor, Jonathan E |
| Thesis advisor | Taylor, Jonathan E |
| Thesis advisor | Candès, Emmanuel J. (Emmanuel Jean) |
| Thesis advisor | Hastie, Trevor |
| Advisor | Candès, Emmanuel J. (Emmanuel Jean) |
| Advisor | Hastie, Trevor |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Ryan Joseph Tibshirani. |
|---|---|
| Note | Submitted to the Department of Statistics. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2011. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2011 by Ryan Joseph Tibshirani
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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