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ROOPSD: R Object Oriented Programming for Statistical Distribution

Statistical distribution in OOP (Object Oriented Programming) way. This package proposes a R6 class interface to classic statistical distribution, and new distributions can be easily added with the class AbstractDist. A useful point is the generic fit() method for each class, which uses a maximum likelihood estimation to find the parameters of a dataset, see, e.g. Hastie, T. and al (2009) <isbn:978-0-387-84857-0>. Furthermore, the rv_histogram class gives a non-parametric fit, with the same accessors that for the classic distribution. Finally, three random generators useful to build synthetic data are given: a multivariate normal generator, an orthogonal matrix generator, and a symmetric positive definite matrix generator, see Mezzadri, F. (2007) <doi:10.48550/arXiv.math-ph/0609050>.

Version: 0.3.9
Depends: R (≥ 3.3)
Imports: methods, R6, Lmoments, numDeriv
Published: 2023-09-11
DOI: 10.32614/CRAN.package.ROOPSD
Author: Yoann Robin [aut, cre]
Maintainer: Yoann Robin <yoann.robin.k at gmail.com>
License: CeCILL-2
URL: https://github.com/yrobink/ROOPSD
NeedsCompilation: no
In views: Distributions
CRAN checks: ROOPSD results

Documentation:

Reference manual: ROOPSD.pdf

Downloads:

Package source: ROOPSD_0.3.9.tar.gz
Windows binaries: r-devel: ROOPSD_0.3.9.zip, r-release: ROOPSD_0.3.9.zip, r-oldrel: ROOPSD_0.3.9.zip
macOS binaries: r-release (arm64): ROOPSD_0.3.9.tgz, r-oldrel (arm64): ROOPSD_0.3.9.tgz, r-release (x86_64): ROOPSD_0.3.9.tgz, r-oldrel (x86_64): ROOPSD_0.3.9.tgz
Old sources: ROOPSD archive

Reverse dependencies:

Reverse imports: ftsa, SBCK

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.