Use Newton's method and coordinate descent to solve the regularized inverse covariance matrix estimation problem. Please refer to: Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation, Cho-Jui Hsieh, Matyas A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar, Advances in Neural Information Processing Systems 24, 2011, p. 2330–2338.
Version: | 1.1 |
Depends: | R (≥ 2.10) |
Published: | 2012-05-17 |
Author: | Cho-Jui Hsieh [aut], Matyas A. Sustik [aut, cre], Inderjit S. Dhillon [aut], Pradeep Ravikumar [aut] |
Maintainer: | Matyas A. Sustik <sustik at cs.utexas.edu> |
BugReports: | sustik@cs.utexas.edu |
License: | GPL-3 |
URL: | http://www.r-project.org, http://www.cs.utexas.edu/users/sustik/QUIC |
NeedsCompilation: | yes |
Citation: | QUIC citation info |
In views: | gR |
CRAN checks: | QUIC results |
Reference manual: | QUIC.pdf |
Package source: | QUIC_1.1.tar.gz |
Windows binaries: | r-devel: QUIC_1.1.zip, r-release: QUIC_1.1.zip, r-oldrel: QUIC_1.1.zip |
OS X El Capitan binaries: | r-release: QUIC_1.1.tgz |
OS X Mavericks binaries: | r-oldrel: QUIC_1.1.tgz |
Old sources: | QUIC archive |
Reverse depends: | abundant, MRCE, rsggm |
Reverse imports: | SparseTSCGM |
Reverse suggests: | pulsar, scio, stabs |
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