Nothing
Use Newton's method, coordinate descent, and METIS clustering to solve the L1 regularized Gaussian MLE inverse covariance matrix estimation problem.
Package details |
|
---|---|
Author | Khalid B. Kunji [aut, cre], Cho-Jui Hsieh [ctb], Matyas A. Sustik [ctb], Inderjit S. Dhillon [ctb], Pradeep Ravikumar [ctb], Tuo Zhao [ctb], Xingguo Li [ctb], Han Liu [ctb], Kathryn Roeder [ctb], John Lafferty [ctb], Larry Wasserman [ctb], George Karypis [ctb], Melissa O'Neill [ctb], Richard Henderson [ctb] |
Maintainer | Khalid B. Kunji <kkunji@hbku.edu.qa> |
License | GPL (>= 3) | file LICENSE |
Version | 1.1-13 |
URL | https://www.r-project.org https://bigdata.oden.utexas.edu/software/1035/ http://glaros.dtc.umn.edu/gkhome/views/metis https://www.pcg-random.org/download.html https://gcc.gnu.org/projects/gomp/ |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.