\name{chamae3}
\docType{data}
\alias{chamae3}
\title{Life History Data on Chamaecrista fasciculata}
\description{
  Data on life history traits for the partridge pea
  \emph{Chamaecrista fasciculata}
}
\usage{data(chamae3)}
\format{
  A data frame with records for 2239 plants.
  Data are already in \dQuote{long} format; no need to reshape.
   \describe{
    \item{resp}{Response vector.}
    \item{varb}{Categorical.  Gives node of graphical model corresponding
      to each component of \code{resp}.  See details below.}
    \item{root}{All ones.  Root variables for graphical model.}
    \item{id}{Categorical.  Indicates individual plants.}
    \item{fit}{Zero-or-one-valued.  Indicates \dQuote{fitness} nodes of the
      graph.}
    \item{SIRE}{Categorical.  Sire.}
    \item{DAM}{Categorical.  Dam.}
    \item{SITE}{Categorical.  Experiment site.}
    \item{POP}{Categorical.  Population of sire and dam.}
    \item{ROW}{Numerical.  Row.  Position in site.}
    \item{BLK}{Categorical.  Block within site.}
  }
}
\details{
The levels of \code{varb} indicate nodes of the graphical model to which
the corresponding elements of the response vector \code{resp} belong.
This is the typical \dQuote{long} format produced by the R \code{reshape}
function.  For each individual, there are several response variables.
All response variables are combined in one vector \code{resp}.
The variable \code{varb} indicates which \dQuote{original} variable
the number was for.  The variable \code{id} indicates which individual
the number was for.  The levels of \code{varb}, which are the names
of the \dQuote{original} variables are
\describe{
  \item{fecund}{Fecundity.  Bernoulli, One if any fruit, zero if no fruit.}
  \item{fruit}{Integer.  Number of fruits observed.}
}
}
\source{
Julie Etterson
\url{https://sites.google.com/d.umn.edu/dr-julie-r-etterson/home}
}
\references{
These data are a subset of data previously analyzed by non-aster methods in the following.

Etterson, J. R. (2004).
Evolutionary potential of \emph{Chamaecrista fasciculata} in
    relation to climate change.  II. Genetic architecture of three
    populations reciprocally planted along an environmental gradient in the
    great plains.
\emph{Evolution}, \bold{58}, 1459--1471.
\doi{10.1111/j.0014-3820.2004.tb01727.x}.

These data were reanalyzed by aster methods in the following.

Geyer, C. J., Ridley, C. E., Latta, R. G., Etterson, J. R.,
    and Shaw, R. G. (2013)
Local Adaptation and Genetic Effects on Fitness: Calculations
    for Exponential Family Models with Random Effects.
\emph{Annals of Applied Statistics}, \bold{7}, 1778--1795.
\doi{10.1214/13-AOAS653}.
}
\examples{
data(chamae3)
### wide version
\dontrun{
### CRAN policy says examples must take < 5 sec.  This doesn't.
foo <- chamae3
### delete fit because it makes no sense in wide version
foo$fit <- NULL
chamae3w <- reshape(foo, direction = "wide", timevar = "varb",
    v.names = "resp", varying = list(levels(chamae3$varb)))
}
}
\keyword{datasets}