doi:10.48550/arXiv.2505.22507>.">

lognGPD: Estimation of a Lognormal - Generalized Pareto Mixture (original) (raw)

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
URL: https://github.com/marco-bee/lognGPD
NeedsCompilation: no
Materials: README, NEWS
In views: Distributions
CRAN checks: lognGPD results

Documentation:

Reference manual: lognGPD.html , <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

Linking:

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