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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "adlaplace" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'adlaplace: Laplace Approximations Using Automatic Differentiation'
version: 0.7.4
abstract: Computes Laplace-approximate maximum likelihood for hierarchical and latent
  Gaussian models. A formula interface specifies observation densities (e.g. Gaussian,
  negative Binomial), fixed effects, and random terms (independent effects, smoothing
  terms). Customized response distributions and models for random effects can be specified
  through a low-level interface or by writing interoperable packages. Derivatives
  are computed using automatic differentiation with 'CppAD', and used in trust region
  optimization to find modes of random effects. Derivatives of the Laplace approximation
  of the log-likelihood are computed using third order contractions and is compatible
  with custom atomics. The approach follows Kristensen, Nielsen, Berg, Skaug, and
  Bell (2016) <https://doi.org/10.18637/jss.v070.i05>.
authors:
- family-names: Brown
  given-names: Patrick
  email: patrick.borgnine@gmail.com
repository: https://cran.r-universe.dev
commit: 907575b4f49c0af42576f5404b227b3a4f4a656d
date-released: '2026-10-08'
contact:
- family-names: Brown
  given-names: Patrick
  email: patrick.borgnine@gmail.com