Package: gclm 0.0.1.9999

gclm: Graphical Continuous Lyapunov Models

Estimation of covariance matrices as solutions of continuous time Lyapunov equations. Sparse coefficient matrix and diagonal noise are estimated with a proximal gradient method for an l1-penalized loss minimization problem. Varando G, Hansen NR (2020) <arxiv:2005.10483>.

Authors:Gherardo Varando [aut, cre, cph], Niels Richard Hansen [aut]

gclm_0.0.1.9999.tar.gz
gclm_0.0.1.9999.zip(r-4.7-x86_64)gclm_0.0.1.9999.zip(r-4.7-arm64)gclm_0.0.1.9999.zip(r-4.6-x86_64)gclm_0.0.1.9999.zip(r-4.6-arm64)gclm_0.0.1.9999.zip(r-4.5-x86_64)
gclm_0.0.1.9999.tgz(r-4.6-x86_64)gclm_0.0.1.9999.tgz(r-4.6-arm64)gclm_0.0.1.9999.tgz(r-4.5-x86_64)gclm_0.0.1.9999.tgz(r-4.5-arm64)
gclm_0.0.1.9999.tar.gz(r-4.7-arm64)gclm_0.0.1.9999.tar.gz(r-4.7-x86_64)gclm_0.0.1.9999.tar.gz(r-4.6-arm64)gclm_0.0.1.9999.tar.gz(r-4.6-x86_64)
gclm_0.0.1.9999.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
gclm/json (API)

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

Bug tracker:https://github.com/gherardovarando/gclm/issues

Uses libs:
  • openblas– Optimized BLAS

On CRAN:

Conda:

openblas

2.70 score 2 scripts 305 downloads 5 exports 0 dependencies

Last updated from:d20bd5d07d. Checks:13 WARNING, 1 ERROR, 1 OK. Indexed: yes.

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wasm-releaseOK65

Exports:B0clyapgclmgclm.lowertrigclm.path

Dependencies: