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cff-version: 1.2.0
message: 'To cite package "femtograd" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'femtograd: Automatic Differentiation for Statistical Computing'
version: 0.3.1
doi: 10.32614/CRAN.package.femtograd
identifiers:
- type: url
  value: https://queelius.r-universe.dev/femtograd
abstract: Provides automatic differentiation via reverse-mode AD (backpropagation)
  for first-order gradients and forward-over-reverse AD for Hessian computation. Includes
  log-likelihood functions for exponential family distributions (normal, exponential,
  Poisson, binomial, gamma, beta, negative binomial, Weibull, Pareto), MLE optimization
  via fit() with base R generics (coef, vcov, confint, logLik, AIC/BIC), hypothesis
  testing (likelihood ratio, Wald), profile likelihood, bootstrap inference, and model
  diagnostics. Designed for pedagogy and modern statistics rather than large-scale
  ML.
authors:
- family-names: Towell
  given-names: Alexander
  email: lex@metafunctor.com
  orcid: https://orcid.org/0000-0001-6443-9897
repository: https://queelius.r-universe.dev
repository-code: https://github.com/queelius/femtograd
commit: 50193c0c1dcbd1ffc0d1c268500616d6a5a3f2bc
url: https://queelius.github.io/femtograd/
date-released: '2026-04-14'
contact:
- family-names: Towell
  given-names: Alexander
  email: lex@metafunctor.com
  orcid: https://orcid.org/0000-0001-6443-9897
keywords:
- automatic-differentiation
- backpropagation
- maximum-likelihood
- hessian
- statistics
- computational-graph
- inference
- pedagogy