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\name{predict.ecoNP}
\alias{predict.ecoNP}
\alias{predict.ecoNPX}
\title{Out-of-Sample Posterior Prediction under the
Nonparametric Bayesian Model for Ecological Inference in 2x2 Tables}
\description{
Obtains out-of-sample posterior predictions under the fitted
nonparametric Bayesian model for ecological
inference. \code{predict} method for class \code{ecoNP} and \code{ecoNPX}.
}
\usage{
\method{predict}{ecoNP}(object, newdraw = NULL, subset = NULL, obs = NULL,
verbose = FALSE, ...)
\method{predict}{ecoNPX}(object, newdraw = NULL, subset = NULL, obs = NULL,
cond = FALSE, verbose = FALSE, ...)
}
\arguments{
\item{object}{An output object from \code{ecoNP}.}
\item{newdraw}{An optional list containing two matrices (or three
dimensional arrays for the nonparametric model) of MCMC draws
of \eqn{\mu} and \eqn{\Sigma}. Those elements should be named as
\code{mu} and \code{Sigma}, respectively. The default is the
original MCMC draws stored in \code{object}.
}
\item{subset}{A scalar or numerical vector specifying the row
number(s) of \code{mu} and \code{Sigma} in the output object from
\code{eco}. If specified, the posterior draws of parameters for
those rows are used for posterior prediction. The default is
\code{NULL} where all the posterior draws are used.
}
\item{obs}{An integer or vector of integers specifying the observation
number(s) whose posterior draws will be used for predictions. The
default is \code{NULL} where all the observations in the data set
are selected.
}
\item{cond}{logical. If \code{TRUE}, then the conditional prediction
will made for the parametric model with contextual effects. The
default is \code{FALSE}.
}
\item{verbose}{logical. If \code{TRUE}, helpful messages along with a
progress report on the Monte Carlo sampling from the posterior
predictive distributions are printed on the screen. The default is
\code{FALSE}.
}
\item{...}{further arguments passed to or from other methods.}
}
\details{The posterior predictive values are computed using the
Monte Carlo sample stored in the \code{eco} or \code{ecoNP} output
(or other sample if
\code{newdraw} is specified). Given each Monte Carlo sample of the
parameters, we sample the vector-valued latent variable from the
appropriate multivariate Normal distribution. Then, we apply the
inverse logit transformation to obtain the predictive values of
proportions, \eqn{W}. The computation may be slow (especially for the
nonparametric model) if a large Monte Carlo sample of the model
parameters is used. In either case, setting \code{verbose = TRUE} may
be helpful in monitoring the progress of the code.
}
\value{
\code{predict.eco} yields a matrix of class \code{predict.eco}
containing the Monte Carlo sample from the posterior predictive
distribution of inner cells of ecological
tables. \code{summary.predict.eco} will summarize the output, and
\code{print.summary.predict.eco} will print the summary.
}
\seealso{\code{eco}, \code{ecoNP}, \code{summary.eco},
\code{summary.ecoNP}}
\author{
Kosuke Imai, Department of Politics, Princeton University,
\email{kimai@Princeton.Edu}, \url{http://imai.princeton.edu};
Ying Lu, Department of Sociology, University of Colorado at Boulder,
\email{ying.lu@Colorado.Edu}
}
\keyword{methods}
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