Package: femtograd
Title: Automatic Differentiation for Statistical Computing
Version: 0.3.1
Authors@R: 
    person("Alexander", "Towell", , "lex@metafunctor.com", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0001-6443-9897"))
Maintainer: Alexander Towell <lex@metafunctor.com>
Description: 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.
License: GPL (>= 3)
URL: https://queelius.github.io/femtograd/,
        https://github.com/queelius/femtograd,
        https://queelius.r-universe.dev/femtograd
BugReports: https://github.com/queelius/femtograd/issues
X-schema.org-keywords: automatic-differentiation, backpropagation,
        maximum-likelihood, hessian, statistics, computational-graph,
        inference, pedagogy
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Imports: R6
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
Config/testthat/edition: 3
Repository: https://queelius.r-universe.dev
Date/Publication: 2026-04-14 06:34:18 UTC
RemoteUrl: https://github.com/queelius/femtograd
RemoteRef: HEAD
RemoteSha: 50193c0c1dcbd1ffc0d1c268500616d6a5a3f2bc
NeedsCompilation: no
Packaged: 2026-07-13 08:08:09 UTC; root
Author: Alexander Towell [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-6443-9897>)