Package: finbipartite 0.1.0
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).
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finbipartite_0.1.0.tar.gz
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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:OK: 1 NOTE: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 21 2024 |
R-4.5-win | NOTE | Nov 21 2024 |
R-4.5-linux | NOTE | Nov 21 2024 |
R-4.4-win | NOTE | Nov 21 2024 |
R-4.4-mac | NOTE | Nov 21 2024 |
R-4.3-win | NOTE | Nov 21 2024 |
R-4.3-mac | NOTE | Nov 21 2024 |
Exports:learn_bipartite_graph_nielearn_connected_bipartite_graph_pgdlearn_heavy_tail_bipartite_graph_pgdlearn_heavy_tail_kcomp_bipartite_graph
Dependencies:bitbit64clicrayonCVXRdata.tableECOSolveRgluegmphmsjsonlitelatticelifecycleMASSMatrixmvtnormosqppkgconfigprettyunitsprogressquadprogR6RcppRcppArmadilloRcppEigenrlangrlistRmpfrscsspectralGraphTopologyvctrsXMLyaml