Package: PoisNonNor 1.6.3

PoisNonNor: Simultaneous Generation of Count and Continuous Data

Generation of count (assuming Poisson distribution) and continuous data (using Fleishman polynomials) simultaneously. The details of the method are explained in Demirtas et al. (2012) <doi:10.1002/sim.5362>.

Authors:Hakan Demirtas, Yaru Shi, Rawan Allozi, Ran Gao

PoisNonNor_1.6.3.tar.gz
PoisNonNor_1.6.3.zip(r-4.7-any)PoisNonNor_1.6.3.zip(r-4.6-any)PoisNonNor_1.6.3.zip(r-4.5-any)
PoisNonNor_1.6.3.tgz(r-4.6-any)PoisNonNor_1.6.3.tgz(r-4.5-any)
PoisNonNor_1.6.3.tar.gz(r-4.7-any)PoisNonNor_1.6.3.tar.gz(r-4.6-any)
PoisNonNor_1.6.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
PoisNonNor/json (API)

# Install 'PoisNonNor' in R:
install.packages('PoisNonNor', repos = c('https://bernice0321.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 10 scripts 304 downloads 12 exports 6 dependencies

Last updated from:df47cdab49. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK107
source / vignettesOK139
linux-releaseOK100
macos-releaseOK97
macos-oldrelOK122
windows-develOK75
windows-releaseOK76
windows-oldrelOK74
wasm-releaseOK74

Exports:bounds.corr.GSC.NNbounds.corr.GSC.NNPbounds.corr.GSC.PPfleishman.rootsintercor.allintercor.NNintercor.NNPintercor.PPParam.fleishmanRNG_P_NNRNG.P.NNValidate.correlation

Dependencies:BBcorpcorlatticeMASSMatrixquadprog