Package: humanleague 2.3.2

humanleague: Synthetic Population Generator

Generates high-entropy integer synthetic populations from marginal and (optionally) seed data using quasirandom sampling, in arbitrary dimensionality (Smith, Lovelace and Birkin (2017) <doi:10.18564/jasss.3550>). The package also provides an implementation of the Iterative Proportional Fitting (IPF) algorithm (Zaloznik (2011) <doi:10.13140/2.1.2480.9923>).

Authors:Andrew Smith [aut, cre], Steven Johnson [ctb], Massachusetts Institute of Technology [cph], John Burkhardt [ctb, cph], G Bhattacharjee [ctb]

humanleague_2.3.2.tar.gz
humanleague_2.3.2.zip(r-4.7)humanleague_2.3.2.zip(r-4.6)humanleague_2.3.2.zip(r-4.5)
humanleague_2.3.2.tgz(r-4.6-x86_64)humanleague_2.3.2.tgz(r-4.6-arm64)humanleague_2.3.2.tgz(r-4.5-x86_64)humanleague_2.3.2.tgz(r-4.5-arm64)
humanleague_2.3.2.tar.gz(r-4.7-arm64)humanleague_2.3.2.tar.gz(r-4.7-x86_64)humanleague_2.3.2.tar.gz(r-4.6-arm64)humanleague_2.3.2.tar.gz(r-4.6-x86_64)
humanleague_2.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
humanleague/json (API)

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

Bug tracker:https://github.com/virgesmith/humanleague/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

c-plus-plus-11microsynthesisnodejspython3quasirandomsampling-methodscpp

5.27 score 19 stars 13 scripts 606 downloads 8 exports 1 dependencies

Last updated from:9ff352db1e. Checks:11 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE159
linux-devel-x86_64NOTE140
source / vignettesOK183
linux-release-arm64NOTE147
linux-release-x86_64NOTE142
macos-release-arm64NOTE125
macos-release-x86_64NOTE584
macos-oldrel-arm64NOTE138
macos-oldrel-x86_64NOTE525
windows-develNOTE130
windows-releaseNOTE120
windows-oldrelNOTE130
wasm-releaseOK116

Exports:flattenintegeriseipfprob2IntFreqqisqisisobolSequenceunitTest

Dependencies:Rcpp