_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-binordnonnor 1.5.2
Propagated dependencies: r-ordnor@2.2.3 r-mvtnorm@1.3-2 r-matrix@1.7-1 r-genord@1.4.0 r-corpcor@1.6.10 r-bb@2019.10-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BinOrdNonNor
Licenses: GPL 2 GPL 3
Synopsis: Concurrent Generation of Binary, Ordinal and Continuous Data
Description:

Generation of samples from a mix of binary, ordinal and continuous random variables with a pre-specified correlation matrix and marginal distributions. The details of the method are explained in Demirtas et al. (2012) <DOI:10.1002/sim.5362>.

Total results: 1