eco

R package for ecological inference in 2 × 2 tables

Kosuke Imai, Ying Lu, Aaron Strauss

Research output: Contribution to journalArticle

Abstract

eco is a publicly available R package that implements the Bayesian and likelihood methods proposed in Imai, Lu, and Strauss (2008b) for ecological inference in 2 × 2 tables as well as the method of bounds introduced by (Duncan and Davis 1953). The package ts 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 e ect of data aggregation on parameter estimation and hypothesis testing under the parametric likelihood models. This paper illustrates the usage of eco with several real data examples that are also part of the package.

Original languageEnglish (US)
Pages (from-to)1-23
Number of pages23
JournalJournal of Statistical Software
Volume42
Issue number5
StatePublished - Jun 2011

Fingerprint

2 × 2 Table
Likelihood
Data Aggregation
Markov Chain Monte Carlo Algorithms
Likelihood Methods
Nonparametric Model
Expectation-maximization Algorithm
Bayesian Methods
Bayesian Model
Hypothesis Testing
Parametric Model
Parameter Estimation
Quantify
Model
Prediction
Parameter estimation
Markov processes
Agglomeration
Inference
Testing

Keywords

  • Aggregate data
  • Bayesian inference
  • Bounds
  • Likelihood inference
  • Missing data
  • Missing information

ASJC Scopus subject areas

  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

eco : R package for ecological inference in 2 × 2 tables. / Imai, Kosuke; Lu, Ying; Strauss, Aaron.

In: Journal of Statistical Software, Vol. 42, No. 5, 06.2011, p. 1-23.

Research output: Contribution to journalArticle

Imai, Kosuke ; Lu, Ying ; Strauss, Aaron. / eco : R package for ecological inference in 2 × 2 tables. In: Journal of Statistical Software. 2011 ; Vol. 42, No. 5. pp. 1-23.
@article{f9277f82d16b4f80aeeacd0f410dc6fe,
title = "eco: R package for ecological inference in 2 × 2 tables",
abstract = "eco is a publicly available R package that implements the Bayesian and likelihood methods proposed in Imai, Lu, and Strauss (2008b) for ecological inference in 2 × 2 tables as well as the method of bounds introduced by (Duncan and Davis 1953). The package ts 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 e ect of data aggregation on parameter estimation and hypothesis testing under the parametric likelihood models. This paper illustrates the usage of eco with several real data examples that are also part of the package.",
keywords = "Aggregate data, Bayesian inference, Bounds, Likelihood inference, Missing data, Missing information",
author = "Kosuke Imai and Ying Lu and Aaron Strauss",
year = "2011",
month = "6",
language = "English (US)",
volume = "42",
pages = "1--23",
journal = "Journal of Statistical Software",
issn = "1548-7660",
publisher = "University of California at Los Angeles",
number = "5",

}

TY - JOUR

T1 - eco

T2 - R package for ecological inference in 2 × 2 tables

AU - Imai, Kosuke

AU - Lu, Ying

AU - Strauss, Aaron

PY - 2011/6

Y1 - 2011/6

N2 - eco is a publicly available R package that implements the Bayesian and likelihood methods proposed in Imai, Lu, and Strauss (2008b) for ecological inference in 2 × 2 tables as well as the method of bounds introduced by (Duncan and Davis 1953). The package ts 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 e ect of data aggregation on parameter estimation and hypothesis testing under the parametric likelihood models. This paper illustrates the usage of eco with several real data examples that are also part of the package.

AB - eco is a publicly available R package that implements the Bayesian and likelihood methods proposed in Imai, Lu, and Strauss (2008b) for ecological inference in 2 × 2 tables as well as the method of bounds introduced by (Duncan and Davis 1953). The package ts 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 e ect of data aggregation on parameter estimation and hypothesis testing under the parametric likelihood models. This paper illustrates the usage of eco with several real data examples that are also part of the package.

KW - Aggregate data

KW - Bayesian inference

KW - Bounds

KW - Likelihood inference

KW - Missing data

KW - Missing information

UR - http://www.scopus.com/inward/record.url?scp=79961211548&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79961211548&partnerID=8YFLogxK

M3 - Article

VL - 42

SP - 1

EP - 23

JO - Journal of Statistical Software

JF - Journal of Statistical Software

SN - 1548-7660

IS - 5

ER -