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eco  

Ecological Inference in 2x2 Tables
View on CRAN: Click here


Download and install eco package within the R console
Install from CRAN:
install.packages("eco")

Install from Github:
library("remotes")
install_github("cran/eco")

Install by package version:
library("remotes")
install_version("eco", "4.0-6")



Attach the package and use:
library("eco")
Maintained by
Ying Lu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2004-12-21
Latest Update:
Description:
Implements the Bayesian and likelihood methods proposedin Imai Lu and Strauss 2008 DOI 10.1093panmpm017 and2011 DOI10.18637jss.v042.i05 for ecological inference in 2by 2 tables as well as the method of bounds introduced by Duncan andDavis 1953. The package fits both parametric and nonparametricmodels using either the Expectation-Maximization algorithms forlikelihood models or the Markov chain Monte Carlo algorithms forBayesian models. For all models the individual-level data can bedirectly incorporated into the estimation whenever such data are available.Along with in-sample and out-of-sample predictions the package alsoprovides a functionality which allows one to quantify the effect of dataaggregation on parameter estimation and hypothesis testing under theparametric likelihood models.
How to cite:
Ying Lu (2004). eco: Ecological Inference in 2x2 Tables. R package version 4.0-6, https://cran.r-project.org/web/packages/eco. Accessed 05 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:34), 1.0-1 (2004-12-21 12:20), 1.1-1 (2005-06-16 18:11), 2.1-1 (2005-07-09 12:27), 2.2-1 (2005-09-30 19:22), 2.2-2 (2006-09-24 10:02), 3.0-1 (2007-01-01 15:22), 3.0-2 (2007-01-11 20:41), 3.1-1 (2007-06-28 21:02), 3.1-2 (2009-02-01 11:41), 3.1-4 (2009-07-18 17:41), 3.1-5 (2011-04-26 13:50), 3.1-6 (2012-06-12 08:36), 3.1-7 (2015-03-19 09:46), 4.0-1 (2017-08-01 07:24), 4.0-3 (2022-11-03 23:00), 4.0-4 (2025-10-21 13:10), 4.0-5 (2025-10-23 12:40)
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Functions, R codes and Examples using the eco R package
Full eco package functions and examples
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