#' Compute and display a univariate averaged shifted histogram (polynomial kernel)
#'
#' See \code{\link[ash]{bin1}} & \code{\link[ash]{ash1}} for more information.
#'
#' \if{html}{
#' A sample of the output from \code{stat_ash()}:
#'
#' \figure{statash01.png}{options: width="100\%" alt="Figure: statash01.png"}
#' }
#'
#' \if{latex}{
#' A sample of the output from \code{stat_ash()}:
#'
#' \figure{statash01.png}{options: width=10cm}
#' }
#'
#' @inheritParams ggplot2::geom_area
#' @param geom Use to override the default Geom
#' @param ab half-open interval for bins \emph{[a,b)}. If no value is specified,
#' the range of x is stretched by \code{5\%} at each end and used the
#' interval.
#' @param nbin number of bins desired. Default \code{50}.
#' @param m integer smoothing parameter; Default \code{5}.
#' @param kopt vector of length 2 specifying the kernel, which is proportional
#' to \emph{( 1 - abs(i/m)^kopt(1) )i^kopt(2)}; (2,2)=biweight (default);
#' (0,0)=uniform; (1,0)=triangle; (2,1)=Epanechnikov; (2,3)=triweight.
#' @references David Scott (1992), \emph{"Multivariate Density Estimation,"}
#' John Wiley, (chapter 5 in particular).\cr
#' \cr
#' B. W. Silverman (1986), \emph{"Density Estimation for Statistics
#' and Data Analysis,"} Chapman & Hall.
#' @section Aesthetics:
#' \code{geom_ash} understands the following aesthetics (required aesthetics
#' are in bold):
#' \itemize{
#' \item \strong{\code{x}}
#' \item \code{alpha}
#' \item \code{color}
#' \item \code{fill}
#' \item \code{linetype}
#' \item \code{size}
#' }
#' @section Computed variables:
#' \describe{
#' \item{\code{density}}{ash density estimate}
#' }
#' @export
#' @examples
#' # compare
#' library(gridExtra)
#' set.seed(1492)
#' dat <- data.frame(x=rnorm(100))
#' grid.arrange(ggplot(dat, aes(x)) + stat_ash(),
#' ggplot(dat, aes(x)) + stat_bkde(),
#' ggplot(dat, aes(x)) + stat_density(),
#' nrow=3)
#'
#' cols <- RColorBrewer::brewer.pal(3, "Dark2")
#' ggplot(dat, aes(x)) +
#' stat_ash(alpha=1/2, fill=cols[3]) +
#' stat_bkde(alpha=1/2, fill=cols[2]) +
#' stat_density(alpha=1/2, fill=cols[1]) +
#' geom_rug() +
#' labs(x=NULL, y="density/estimate") +
#' scale_x_continuous(expand=c(0,0)) +
#' theme_bw() +
#' theme(panel.grid=element_blank()) +
#' theme(panel.border=element_blank())
stat_ash <- function(mapping = NULL, data = NULL, geom = "area",
position = "stack",
ab = NULL, nbin = 50, m = 5, kopt = c(2, 2),
na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...) {
layer(
data = data,
mapping = mapping,
stat = StatAsh,
geom = geom,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
na.rm = na.rm,
ab = ab,
nbin = nbin,
m = m,
kopt = kopt,
...
)
)
}
#' Geom Proto
#' @rdname ggalt-ggproto
#' @format NULL
#' @usage NULL
#' @keywords internal
#' @export
StatAsh <- ggproto("StatAsh", Stat,
required_aes = c("x"),
default_aes = aes(y = ..density.., colour = NA, fill = "gray20", size = 0.5,
linetype = 1, alpha = NA),
setup_params = function(data, params) {
if (!is.null(data$y) || !is.null(params$y)) {
stop("stat_ash() must not be used with a y aesthetic.", call. = FALSE)
}
params
},
compute_group = function(data, scales, ab = NULL,
nbin = 50, m = 5, kopt = c(2, 2)) {
if (is.null(ab)) ab <- nicerange(data$x)
bin_res <- ash::bin1(data$x, ab, nbin)
ash_msg <- capture.output(ash_res <- ash1(bin_res))
if (ash_res$ier == 1) message("Estimate nonzero outside interval ab.")
data.frame(x=ash_res$x, density=ash_res$y)
}
)
nicerange <- function (x, beta = 0.1) {
ab <- range(x)
del <- ((ab[2] - ab[1]) * beta)/2
return(c(ab + c(-del, del)))
}
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