Package: covdepGE 1.0.1

Jacob Helwig

covdepGE: Covariate Dependent Graph Estimation

A covariate-dependent approach to Gaussian graphical modeling as described in Dasgupta et al. (2022). Employs a novel weighted pseudo-likelihood approach to model the conditional dependence structure of data as a continuous function of an extraneous covariate. The main function, covdepGE::covdepGE(), estimates a graphical representation of the conditional dependence structure via a block mean-field variational approximation, while several auxiliary functions (inclusionCurve(), matViz(), and plot.covdepGE()) are included for visualizing the resulting estimates.

Authors:Jacob Helwig [cre, aut], Sutanoy Dasgupta [aut], Peng Zhao [aut], Bani Mallick [aut], Debdeep Pati [aut]

covdepGE_1.0.1.tar.gz
covdepGE_1.0.1.tar.gz(r-4.5-noble)covdepGE_1.0.1.tar.gz(r-4.4-noble)
covdepGE_1.0.1.tgz(r-4.4-emscripten)covdepGE_1.0.1.tgz(r-4.3-emscripten)
covdepGE.pdf |covdepGE.html
covdepGE/json (API)

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

Peer review:

Bug tracker:https://github.com/jacobhelwig/covdepge/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

openblascppopenmp

2.41 score 51 scripts 184 downloads 4 exports 43 dependencies

Last updated 2 years agofrom:d7aaef416c. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 02 2024
R-4.5-linux-x86_64NOTEDec 02 2024

Exports:covdepGEgenerateDatainclusionCurvematViz

Dependencies:clicodetoolscolorspacedoParallelfansifarverforeachggplot2glmnetgluegtableisobanditeratorslabelinglatex2explatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloRcppEigenreshape2rlangscalesshapestringistringrsurvivaltibbleutf8vctrsviridisLitewithr