Package: finbipartite 0.1.0
Ze Vinicius
finbipartite: Learning Bipartite Graphs: Heavy Tails and Multiple Components
Learning bipartite and k-component bipartite graphs from financial datasets. This package contains implementations of the algorithms described in the paper: Cardoso JVM, Ying J, and Palomar DP (2022). <https://openreview.net/pdf?id=WNSyF9qZaMd> "Learning bipartite graphs: heavy tails and multiple components, Advances in Neural Informations Processing Systems" (NeurIPS).
Authors:
finbipartite_0.1.0.tar.gz
finbipartite_0.1.0.zip(r-4.5)finbipartite_0.1.0.zip(r-4.4)finbipartite_0.1.0.zip(r-4.3)
finbipartite_0.1.0.tgz(r-4.4-any)finbipartite_0.1.0.tgz(r-4.3-any)
finbipartite_0.1.0.tar.gz(r-4.5-noble)finbipartite_0.1.0.tar.gz(r-4.4-noble)
finbipartite_0.1.0.tgz(r-4.4-emscripten)finbipartite_0.1.0.tgz(r-4.3-emscripten)
finbipartite.pdf |finbipartite.html✨
finbipartite/json (API)
| # Install 'finbipartite' in R: |
| install.packages('finbipartite', repos = c('https://convexfi.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/convexfi/bipartite/issues
Last updated 2 years agofrom:f39c2baac3. Checks:1 OK, 6 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Jan 20 2025 |
| R-4.5-win | NOTE | Jan 20 2025 |
| R-4.5-linux | NOTE | Jan 20 2025 |
| R-4.4-win | NOTE | Jan 20 2025 |
| R-4.4-mac | NOTE | Jan 20 2025 |
| R-4.3-win | NOTE | Jan 20 2025 |
| R-4.3-mac | NOTE | Jan 20 2025 |
Exports:learn_bipartite_graph_nielearn_connected_bipartite_graph_pgdlearn_heavy_tail_bipartite_graph_pgdlearn_heavy_tail_kcomp_bipartite_graph
Dependencies:bitbit64clicrayonCVXRdata.tableECOSolveRgluegmphmsjsonlitelatticelifecycleMASSMatrixmvtnormosqppkgconfigprettyunitsprogressquadprogR6RcppRcppArmadilloRcppEigenrlangrlistRmpfrscsspectralGraphTopologyvctrsXMLyaml
