rIsing: High-Dimensional Ising Model Selection
Fits an Ising model to a binary dataset using L1 regularized
logistic regression and extended BIC. Also includes a fast lasso logistic
regression function for high-dimensional problems. Uses the 'libLBFGS'
optimization library by Naoaki Okazaki.
| Version: |
0.1.0 |
| Depends: |
R (≥ 3.1.0) |
| Imports: |
Rcpp (≥ 0.12.8), data.table (≥ 1.9.6) |
| LinkingTo: |
Rcpp, RcppEigen (≥ 0.3.2.9) |
| Suggests: |
igraph, IsingSampler |
| Published: |
2016-11-25 |
| Author: |
Pratik Ramprasad [aut, cre],
Jorge Nocedal [ctb, cph],
Naoaki Okazaki [ctb, cph] |
| Maintainer: |
Pratik Ramprasad <pratik.ramprasad at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| CRAN checks: |
rIsing results |
Documentation:
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