Package: crandep 0.3.13

Clement Lee

crandep: Network Analysis of Dependencies of CRAN Packages

The dependencies of CRAN packages can be analysed in a network fashion. For each package we can obtain the packages that it depends, imports, suggests, etc. By iterating this procedure over a number of packages, we can build, visualise, and analyse the dependency network, enabling us to have a bird's-eye view of the CRAN ecosystem. One aspect of interest is the number of reverse dependencies of the packages, or equivalently the in-degree distribution of the dependency network. This can be fitted by the power law and/or an extreme value mixture distribution <doi:10.1111/stan.12355>, of which functions are provided.

Authors:Clement Lee [aut, cre]

crandep_0.3.13.tar.gz
crandep_0.3.13.tar.gz(r-4.7-arm64)crandep_0.3.13.tar.gz(r-4.7-x86_64)crandep_0.3.13.tar.gz(r-4.6-arm64)crandep_0.3.13.tar.gz(r-4.6-x86_64)
crandep_0.3.13.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
crandep/json (API)
NEWS

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

Bug tracker:https://github.com/clement-lee/crandep/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

openblascpp

3.64 score 29 scripts 321 downloads 23 exports 25 dependencies

Last updated from:e0f5048e5d. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK155
linux-devel-x86_64OK196
source / vignettesOK381
linux-release-arm64OK162
linux-release-x86_64OK155
wasm-releaseOK139

Exports:df_to_graphdmix2dmix3dpolget_depget_dep_all_packagesget_graph_all_packagesmarg_powmcmc_mix1mcmc_mix1_wrappermcmc_mix2mcmc_mix2_wrappermcmc_mix3mcmc_mix3_wrappermcmc_polmcmc_pol_wrapperobtain_u_set_mix1obtain_u_set_mix2obtain_u_set_mix2_constrainedobtain_u_set_mix3Smix2Smix3Spol

Dependencies:clicpp11dplyrgenericsgluegsligraphlatticelifecyclemagrittrMatrixpillarpkgconfigpracmaR6RcppRcppArmadillorlangstringistringrtibbletidyselectutf8vctrswithr

Introduction to crandep

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Jun 11 2026.

Last update: 2024-12-06
Started: 2020-05-16

Modelling the number of reverse dependencies

Rendered fromdegree.Rmdusingknitr::rmarkdownon Jun 11 2026.

Last update: 2025-05-02
Started: 2020-07-19

The dependency network of all CRAN packages

Rendered fromcran.Rmdusingknitr::rmarkdownon Jun 11 2026.

Last update: 2025-06-16
Started: 2020-08-11

Readme and manuals

Help Manual

Help pageTopics
Citation network of CHI paperschi_citations
Dependencies of CRAN packagescran_dependencies
Construct the giant component of the network from two data framesdf_to_graph
Probability mass function (PMF) of 2-component discrete extreme value mixture distributiondmix2
Probability mass function (PMF) of 3-component discrete extreme value mixture distributiondmix3
Probability mass function (PMF) of Zipf-polylog distributiondpol
Multiple types of dependenciesget_dep
Dependencies of all CRAN packagesget_dep_all_packages
Graph of dependencies of all CRAN packagesget_graph_all_packages
Marginal log-likelihood and posterior density of discrete power law via numerical integrationmarg_pow
Markov chain Monte Carlo for TZP-power-law mixturemcmc_mix1
Wrapper of mcmc_mix1mcmc_mix1_wrapper
Markov chain Monte Carlo for 2-component discrete extreme value mixture distributionmcmc_mix2
Wrapper of mcmc_mix2mcmc_mix2_wrapper
Markov chain Monte Carlo for 3-component discrete extreme value mixture distributionmcmc_mix3
Wrapper of mcmc_mix3mcmc_mix3_wrapper
Markov chain Monte Carlo for Zipf-polylog distributionmcmc_pol
Wrapper of mcmc_polmcmc_pol_wrapper
Obtain set of thresholds with high posterior density for the TZP-power-law mixture modelobtain_u_set_mix1
Obtain set of thresholds with high posterior density for the 2-component mixture modelobtain_u_set_mix2
Obtain set of thresholds with high posterior density for the constrained 2-component mixture modelobtain_u_set_mix2_constrained
Obtain set of thresholds with high posterior density for the 3-component mixture modelobtain_u_set_mix3
Survival function of 2-component discrete extreme value mixture distributionSmix2
Survival function of 3-component discrete extreme value mixture distributionSmix3
Survival function of Zipf-polylog distributionSpol