Package: fingraph 0.1.0

Ze Vinicius

fingraph: Learning Graphs for Financial Markets

Learning graphs for financial markets with optimization algorithms. This package contains implementations of the algorithms described in the paper: Cardoso JVM, Ying J, and Palomar DP (2021) <https://papers.nips.cc/paper/2021/hash/a64a034c3cb8eac64eb46ea474902797-Abstract.html> "Learning graphs in heavy-tailed markets", Advances in Neural Informations Processing Systems (NeurIPS).

Authors:Ze Vinicius [cre, aut]

fingraph_0.1.0.tar.gz
fingraph_0.1.0.zip(r-4.5)fingraph_0.1.0.zip(r-4.4)fingraph_0.1.0.zip(r-4.3)
fingraph_0.1.0.tgz(r-4.5-any)fingraph_0.1.0.tgz(r-4.4-any)fingraph_0.1.0.tgz(r-4.3-any)
fingraph_0.1.0.tar.gz(r-4.5-noble)fingraph_0.1.0.tar.gz(r-4.4-noble)
fingraph_0.1.0.tgz(r-4.4-emscripten)
fingraph.pdf |fingraph.html
fingraph/json (API)

# Install 'fingraph' in R:
install.packages('fingraph', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/convexfi/fingraph/issues

On CRAN:

Conda:

archivedpackagesr-universe

2.40 score 5 stars 192 downloads 3 exports 24 dependencies

Last updated 14 days agofrom:70bb222f45 (on package/fingraph). Checks:1 OK, 7 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 01 2025
R-4.5-winNOTEMar 01 2025
R-4.5-macNOTEMar 01 2025
R-4.5-linuxNOTEMar 01 2025
R-4.4-winNOTEMar 01 2025
R-4.4-macNOTEMar 01 2025
R-4.3-winNOTEMar 01 2025
R-4.3-macNOTEMar 01 2025

Exports:learn_connected_graphlearn_kcomp_heavytail_graphlearn_regular_heavytail_graph

Dependencies:clicrayondata.tablegluehmsjsonlitelatticelifecycleMASSMatrixmvtnormpkgconfigprettyunitsprogressR6RcppRcppArmadilloRcppEigenrlangrlistspectralGraphTopologyvctrsXMLyaml