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ginormal: Generalized Inverse Normal Distribution Density and Generation

Density function and generation of random variables from the Generalized Inverse Normal (GIN) distribution from Robert (1991) <doi:10.1016/0167-7152(91)90174-P>. Also provides density functions and generation from the GIN distribution truncated to positive or negative reals. Theoretical guarantees supporting the sampling algorithms and an application to Bayesian estimation of network formation models can be found in the working paper Ding, Estrada and Montoya-Blandón (2023) <https://www.smontoyablandon.com/publication/networks/network_externalities.pdf>.

Version: 0.0.2
Depends: R (≥ 3.5.0)
Imports: BAS
Published: 2023-08-27
Author: Santiago Montoya-Blandón ORCID iD [cre, aut], Cheng Ding [aut], Juan Estrada ORCID iD [aut], Zhilang Xia [aut], Shanjie Zhang [ctb], Jianming Jin [ctb]
Maintainer: Santiago Montoya-Blandón <Santiago.Montoya-Blandon at glasgow.ac.uk>
BugReports: https://github.com/smonto2/ginormal/issues
License: GPL (≥ 3)
URL: https://github.com/smonto2/ginormal
NeedsCompilation: yes
Materials: README
In views: Distributions
CRAN checks: ginormal results

Documentation:

Reference manual: ginormal.pdf

Downloads:

Package source: ginormal_0.0.2.tar.gz
Windows binaries: r-devel: ginormal_0.0.2.zip, r-release: ginormal_0.0.2.zip, r-oldrel: ginormal_0.0.2.zip
macOS binaries: r-release (arm64): ginormal_0.0.2.tgz, r-oldrel (arm64): ginormal_0.0.2.tgz, r-release (x86_64): ginormal_0.0.2.tgz, r-oldrel (x86_64): ginormal_0.0.2.tgz
Old sources: ginormal archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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