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univariateML: Maximum Likelihood Estimation for Univariate Densities

User-friendly maximum likelihood estimation (Fisher (1921) <doi:10.1098/rsta.1922.0009>) of univariate densities.

Version: 1.1.1
Depends: R (≥ 2.10)
Imports: assertthat, extraDistr, tibble, logitnorm, actuar, nakagami, fGarch
Suggests: testthat, knitr, rmarkdown, markdown, copula, dplyr, covr
Published: 2022-01-25
DOI: 10.32614/CRAN.package.univariateML
Author: Jonas Moss ORCID iD [aut, cre], Thomas Nagler [ctb]
Maintainer: Jonas Moss <jonas.gjertsen at gmail.com>
BugReports: https://github.com/JonasMoss/univariateML/issues
License: MIT + file LICENSE
URL: https://github.com/JonasMoss/univariateML, https://jonasmoss.github.io/univariateML/
NeedsCompilation: no
Citation: univariateML citation info
Materials: README
CRAN checks: univariateML results

Documentation:

Reference manual: univariateML.pdf
Vignettes: Copula Modeling
Distributions
Overview of univariateML

Downloads:

Package source: univariateML_1.1.1.tar.gz
Windows binaries: r-devel: univariateML_1.1.1.zip, r-release: univariateML_1.1.1.zip, r-oldrel: univariateML_1.1.1.zip
macOS binaries: r-release (arm64): univariateML_1.1.1.tgz, r-oldrel (arm64): univariateML_1.1.1.tgz, r-release (x86_64): univariateML_1.1.1.tgz, r-oldrel (x86_64): univariateML_1.1.1.tgz
Old sources: univariateML archive

Reverse dependencies:

Reverse imports: ale, EBcoBART, kdensity, piecenorms, svines

Linking:

Please use the canonical form https://CRAN.R-project.org/package=univariateML to link to this page.

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.