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lognGPD: Estimation of a Lognormal - Generalized Pareto Mixture

Estimation of a lognormal - Generalized Pareto mixture via the Expectation-Maximization algorithm. Computation of bootstrap standard errors is supported and performed via parallel computing. Functions for random number simulation and density evaluation are also available. For more details see Bee and Santi (2025) <doi:10.48550/arXiv.2505.22507>.

Version: 0.1.0
Depends: R (≥ 4.0.0)
Imports: evd, Rdpack, parallel, LNPar, EnvStats
Published: 2025-06-02
DOI: 10.32614/CRAN.package.lognGPD
Author: Marco Bee ORCID iD [aut, cre]
Maintainer: Marco Bee <marco.bee at unitn.it>
BugReports: https://github.com/marco-bee/lognGPD/issues
License: MIT + file LICENSE
URL: https://github.com/marco-bee/lognGPD
NeedsCompilation: no
Materials: README NEWS
In views: Distributions
CRAN checks: lognGPD results

Documentation:

Reference manual: lognGPD.pdf

Downloads:

Package source: lognGPD_0.1.0.tar.gz
Windows binaries: r-devel: lognGPD_0.1.0.zip, r-release: lognGPD_0.1.0.zip, r-oldrel: lognGPD_0.1.0.zip
macOS binaries: r-release (arm64): lognGPD_0.1.0.tgz, r-oldrel (arm64): lognGPD_0.1.0.tgz, r-release (x86_64): lognGPD_0.1.0.tgz, r-oldrel (x86_64): lognGPD_0.1.0.tgz

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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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