Sparse inverse covariance estimation with the graphical lasso |
| |
Authors: | Friedman Jerome Hastie Trevor Tibshirani Robert |
| |
Affiliation: | Department of Statistics, Stanford University, CA 94305, USA. |
| |
Abstract: | We consider the problem of estimating sparse graphs by a lasso penalty applied to the inverse covariance matrix. Using a coordinate descent procedure for the lasso, we develop a simple algorithm--the graphical lasso--that is remarkably fast: It solves a 1000-node problem ( approximately 500,000 parameters) in at most a minute and is 30-4000 times faster than competing methods. It also provides a conceptual link between the exact problem and the approximation suggested by Meinshausen and Bühlmann (2006). We illustrate the method on some cell-signaling data from proteomics. |
| |
Keywords: | |
本文献已被 PubMed 等数据库收录! |
|