File: predict.eco.Rd

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\name{predict.eco}

\alias{predict.eco}
\alias{predict.ecoX}

\title{Out-of-Sample Posterior Prediction under the Parametric Bayesian
Model for Ecological Inference in 2x2 Tables}

\description{
  Obtains out-of-sample posterior predictions under the fitted
  parametric Bayesian model for ecological
  inference. \code{predict} method for class \code{eco} and \code{ecoX}.
}

\usage{
  \method{predict}{eco}(object, newdraw = NULL, subset = NULL,
                   verbose = FALSE, ...)
  \method{predict}{ecoX}(object, newdraw = NULL, subset = NULL,
                   newdata = NULL, cond = FALSE, verbose = FALSE, ...)
}

\arguments{
  \item{object}{An output object from \code{eco} or \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{newdata}{An optional data frame containing a new data set for
    which posterior predictions will be made. The new data set must have
    the same variable names as those in the original data.
  }
  \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{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} 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{predict.ecoNP}}

\author{
  Kosuke Imai, Department of Politics, Princeton University,
  \email{kimai@Princeton.Edu}, \url{http://imai.princeton.edu};
  Ying Lu, Center for Promoting Research Involving Innovative Statistical Methodology (PRIISM), New York University 
  \email{ying.lu@nyu.Edu}
  }

\keyword{methods}