Kosuke Imai <kimai@princeton.edu>,
Ying Lu <yl46@nyu.edu>,
Aaron B Strauss <aaronbstrauss@gmail.com>.
We implement the Bayesian and likelihood methods proposed
in Imai, Lu, and Strauss (2008, 2011) 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.

c(
person("Kosuke", "Imai", , "kimai@Princeton.Edu", c("aut")),
person("Ying", "Lu", , "ying.lu@nyu.edu", c("aut", "cre")),
person("Aaron", "Strauss", , "aaronbstrauss@gmail.com", c("aut")),
person("Hubert", "Jin", , "hubertj@princeton.edu", c("ctb"))
)
Implements the Bayesian and likelihood methods proposed
in Imai, Lu, and Strauss (2008 <DOI: 10.1093/pan/mpm017>) and
(2011 <DOI: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.
Kosuke Imai [aut],
Ying Lu [aut, cre],
Aaron Strauss [aut],
Hubert Jin [ctb]