Qfun

A vector that contains the MLE \(E(W_1)\),\(E(W_2)\),
 \(var(W_1)\),\(var(W_2)\), and \(cov(W_1,W_2)\). Typically it is
the element <code>theta.em</code> of an object of class <code>ecoML</code>.

theta

A vector of sufficient statistics of \(E(W_1)\),
\(E(W_2)\), \(var(W_1)\),\(var(W_2)\), and \(cov(W_1,W_2)\).

suff.stat

A integer representing the sample size.

<code>Qfun</code> returns the complete log-likelihood 
that is used to calculate the fraction of missing information.

models

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.

Qfun: Fitting the Parametric Bayesian Model of Ecological Inference in 2x2 Tables

Description

Usage

Arguments

References

See Also