# --------------------------------------------
# CITATION 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 "eco" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'eco: Ecological Inference in 2x2 Tables'
version: 4.0-6
doi: 10.18637/jss.v042.i05
identifiers:
- type: doi
  value: 10.32614/CRAN.package.eco
abstract: Implements the Bayesian and likelihood methods proposed in Imai, Lu, and
  Strauss (2008 <https://doi.org/10.1093/pan/mpm017>) and (2011 <https://doi.org/10.18637/jss.v042.i05>)
  for ecological inference in 2 by 2 tables as well as the method of bounds introduced
  by Duncan and Davis (1953). The package fits both parametric and nonparametric models
  using either the Expectation-Maximization algorithms (for likelihood models) or
  the Markov chain Monte Carlo algorithms (for Bayesian models). For all models, the
  individual-level data can be directly incorporated into the estimation whenever
  such data are available. Along with in-sample and out-of-sample predictions, the
  package also provides a functionality which allows one to quantify the effect of
  data aggregation on parameter estimation and hypothesis testing under the parametric
  likelihood models.
authors:
- family-names: Imai
  given-names: Kosuke
  email: imai@Harvard.Edu
- family-names: Lu
  given-names: Ying
  email: ying.lu@nyu.edu
- family-names: Strauss
  given-names: Aaron
  email: aaronbstrauss@gmail.com
preferred-citation:
  type: article
  title: 'eco: R Package for Ecological Inference in 2 x 2 Tables'
  authors:
  - family-names: Imai
    given-names: Kosuke
    email: imai@Harvard.Edu
  - family-names: Lu
    given-names: Ying
    email: ying.lu@nyu.edu
  - family-names: Strauss
    given-names: Aaron
    email: aaronbstrauss@gmail.com
  journal: Journal of Statistical Software
  year: '2011'
  volume: '42'
  issue: '5'
  url: https://doi.org/10.18637/jss.v042.i05
  start: '1'
  end: '23'
  doi: 10.18637/jss.v042.i05
repository: https://kosukeimai.r-universe.dev
repository-code: https://github.com/kosukeimai/eco
commit: cb7cbe37a6181a271a11fdf58a4f1d6dba83b8fb
url: https://github.com/kosukeimai/eco
date-released: '2025-12-08'
contact:
- family-names: Imai
  given-names: Kosuke
  email: imai@Harvard.Edu