#' @name cotton_defol
#' @title Number of Bolls in Cotton under Artifitial Defoliation
#' @description These data are the results of a greenshouse factorial
#' experiment performed to evaluate the effect of defoliation on the
#' production of cotton at different growth stages. The experiment
#' is a \eqn{5\times 5} factorial with 5 replications in a complete
#' randomized design. The experimental unit was a pot with 2 cotton
#' plants. The response variable is the number of bolls produced at
#' the end of the crop cycle. The observed number of cotton bolls is
#' a count variable with underdispersion (sample variance less than
#' the sample mean).
#' @format A \code{data.frame} with 125 records and 4 variables,
#' described below.
#'
#' \itemize{
#'
#' \item \code{defol} A numeric factor with 5 levels that represents the
#' (artifitial) levels of defoliation (percent in leaf area removed
#' with scissors) applied for all leaves of the plants.
#'
#' \item \code{phenol} A categorical ordered factor with 5 levels that
#' represents the (phenological) growth stages of the cotton plants
#' in which the levels of defoliation was applied.
#'
#' \item \code{rept} Integer variable that indexes each experimenal unit
#' in each treatment cell.
#'
#' \item \code{bolls} The number of bolls produced (count variable)
#' evaluated at harvest of cotton.
#'
#' }
#' @references Silva, A. M., Degrande, P. E., Suekane, R., Fernandes,
#' M. G., Zeviani, W. M. (2012). Impacto de diferentes níveis de
#' desfolha artificial nos estádios fenológicos do
#' algodoeiro. \strong{Revista de Ciências Agrárias}, 35(1),
#' 163–172.
#' \url{http://www.scielo.mec.pt/pdf/rca/v35n1/v35n1a16.pdf}.
#'
#' Zeviani, W. M., Ribeiro, P. J., Bonat, W. H., Shimakura, S. E.,
#' Muniz, J. A. (2014). The Gamma-count distribution in the analysis
#' of experimental underdispersed data. \strong{Journal of Applied
#' Statistics}, 41(12), 1–11.
#' \url{http://doi.org/10.1080/02664763.2014.922168},
#' \url{http://leg.ufpr.br/doku.php/publications:papercompanions:zeviani-jas2014}.
#' @examples
#'
#' library(lattice)
#' library(latticeExtra)
#'
#' data(cotton_defol)
#' str(cotton_defol)
#'
#' # x11(width = 7, height = 2.8)
#' xyplot(bolls ~ defol | phenol,
#' data = cotton_defol,
#' layout = c(NA, 1),
#' type = c("p", "smooth"),
#' xlab = "Artificial defoliation level",
#' ylab = "Number of bolls produced",
#' xlim = extendrange(c(0:1), f = 0.15),
#' jitter.x = TRUE)
#'
#' # Sample mean and variance in each treatment cell.
#' mv <- aggregate(bolls ~ phenol + defol,
#' data = cotton_defol,
#' FUN = function(x) {
#' c(mean = mean(x), var = var(x))
#' })
#' str(mv)
#'
#' xlim <- ylim <- extendrange(c(mv$bolls), f = 0.05)
#'
#' # Evidence of underdispersion.
#' xyplot(bolls[, "var"] ~ bolls[, "mean"],
#' data = mv,
#' grid = TRUE,
#' aspect = "iso",
#' type = c("p", "r"),
#' xlim = xlim,
#' ylim = ylim,
#' ylab = "Sample variance",
#' xlab = "Sample mean") +
#' layer(panel.abline(a = 0, b = 1, lty = 2))
#'
NULL
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