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likelihood.model: Likelihood-Based Statistical Inference in the Fisherian Tradition

Facilitates building likelihood models in the Fisherian tradition following Richard Royall (1997, ISBN:978-0412044113) "Statistical Evidence: A Likelihood Paradigm". Defines generic methods for working with likelihoods (loglik(), score(), hess_loglik(), fim()) and provides functions for pure likelihood-based inference (support(), relative_likelihood(), likelihood_interval(), profile_loglik()).

Version: 1.0.0
Depends: algebraic.mle (≥ 2.0.0)
Imports: algebraic.dist, generics, stats, numDeriv, boot
Suggests: mvtnorm, testthat (≥ 3.0.0), knitr, rmarkdown
Published: 2026-03-19
DOI: 10.32614/CRAN.package.likelihood.model
Author: Alexander Towell ORCID iD [aut, cre]
Maintainer: Alexander Towell <lex at metafunctor.com>
BugReports: https://github.com/queelius/likelihood.model/issues
License: MIT + file LICENSE
URL: https://github.com/queelius/likelihood.model, https://queelius.github.io/likelihood.model/
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: likelihood.model results

Documentation:

Reference manual: likelihood.model.html , likelihood.model.pdf
Vignettes: Integration with algebraic.mle and algebraic.dist (source, R code)
Exponential Lifetime Model (source, R code)
Getting Started with likelihood.model (source, R code)

Downloads:

Package source: likelihood.model_1.0.0.tar.gz
Windows binaries: r-devel: likelihood.model_1.0.0.zip, r-release: likelihood.model_1.0.0.zip, r-oldrel: likelihood.model_1.0.0.zip
macOS binaries: r-release (arm64): likelihood.model_1.0.0.tgz, r-oldrel (arm64): likelihood.model_1.0.0.tgz, r-release (x86_64): likelihood.model_1.0.0.tgz, r-oldrel (x86_64): likelihood.model_1.0.0.tgz
Old sources: likelihood.model archive

Reverse dependencies:

Reverse imports: flexhaz, likelihood.contr, maskedcauses
Reverse suggests: compositional.mle

Linking:

Please use the canonical form https://CRAN.R-project.org/package=likelihood.model 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.
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