R/plot.OptGS_est.R
In mjg211/OptGS: Optimal and Near-optimal Group-sequential Designs for Clinical Trials with Continuous Outcomes
Defines functions
plot.OptGS_est
Documented in
plot.OptGS_est
#' Plot point estimator performance for two-stage group-sequential clinical
#' trial designs with a normally distributed primary outcome
#'
#' \code{plot.OptGS_est()} plots (conditional and marginal) point estimator bias
#' and residual mean squared error for a specified two-stage group-sequential
#' clinical trial design.
#'
#' @param x An object of class OptGS_est, as returned by \code{\link{est}}.
#' @param ... For compatability with the generic.
#' @param output A \code{\link{logical}} variable indicating whether to return
#' output from the function.
#' @return A \code{\link{list}} containing each of the input variables (subject
#' to internal modification), along with the following elements:
#' \itemize{
#' \item \code{plots}: A \code{\link{list}} containing the available plots.
#' }
#' @examples
#' # For the default two-stage design
#' plot(est(des = opt_gs(), tau = seq(-des$delta, 2*des$delta,
#' length.out = 100)))
#' @seealso \code{\link{est}}
#' @export
plot.OptGS_est <- function(x, ..., output = FALSE) {
##### Input Checking #########################################################
check_OptGS_est(x, "x")
check_logical(output, "output")
##### Main Computations ######################################################
plots <- list()
if (min(x$tau) < 0) {
red <-
tibble::tibble(start = min(x$tau), end = min(0, max(x$tau)))
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
amber <-
tibble::tibble(start = max(0, min(x$tau)),
end = min(x$des$delta, max(x$tau)))
}
if (max(x$tau) > x$des$delta) {
green <-
tibble::tibble(start = max(x$des$delta, min(x$tau)), end = max(x$tau))
}
if (length(unique(x$tau)) > 1) {
plots$`Bias(hat(tau)|tau,1)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`Bias(hat(tau)|tau,1)` <- plots$`Bias(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`Bias(hat(tau)|tau,1)` <- plots$`Bias(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`Bias(hat(tau)|tau,1)` <- plots$`Bias(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`Bias(hat(tau)|tau,1)` <- plots$`Bias(hat(tau)|tau,1)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `Bias(hat(tau)|tau,1)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(Bias), "(", hat(tau), "|", tau,
",1)"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
plots$`Bias(hat(tau)|tau,2)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`Bias(hat(tau)|tau,2)` <- plots$`Bias(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`Bias(hat(tau)|tau,2)` <- plots$`Bias(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`Bias(hat(tau)|tau,2)` <- plots$`Bias(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`Bias(hat(tau)|tau,2)` <- plots$`Bias(hat(tau)|tau,2)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `Bias(hat(tau)|tau,2)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(Bias), "(", hat(tau), "|", tau,
",2)"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
plots$`Bias(hat(tau)|tau)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`Bias(hat(tau)|tau)` <- plots$`Bias(hat(tau)|tau)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`Bias(hat(tau)|tau)` <- plots$`Bias(hat(tau)|tau)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`Bias(hat(tau)|tau)` <- plots$`Bias(hat(tau)|tau)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`Bias(hat(tau)|tau)` <- plots$`Bias(hat(tau)|tau)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `Bias(hat(tau)|tau)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(Bias), "(", hat(tau), "|", tau,
")"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
plots$`RMSE(hat(tau)|tau,1)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`RMSE(hat(tau)|tau,1)` <- plots$`RMSE(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`RMSE(hat(tau)|tau,1)` <- plots$`RMSE(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`RMSE(hat(tau)|tau,1)` <- plots$`RMSE(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`RMSE(hat(tau)|tau,1)` <- plots$`RMSE(hat(tau)|tau,1)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `RMSE(hat(tau)|tau,1)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(RMSE), "(", hat(tau), "|", tau,
",1)"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
plots$`RMSE(hat(tau)|tau,2)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`RMSE(hat(tau)|tau,2)` <- plots$`RMSE(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`RMSE(hat(tau)|tau,2)` <- plots$`RMSE(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`RMSE(hat(tau)|tau,2)` <- plots$`RMSE(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`RMSE(hat(tau)|tau,2)` <- plots$`RMSE(hat(tau)|tau,2)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `RMSE(hat(tau)|tau,2)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(RMSE), "(", hat(tau), "|", tau,
",2)"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
plots$`RMSE(hat(tau)|tau)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`RMSE(hat(tau)|tau)` <- plots$`RMSE(hat(tau)|tau)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`RMSE(hat(tau)|tau)` <- plots$`RMSE(hat(tau)|tau)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`RMSE(hat(tau)|tau)` <- plots$`RMSE(hat(tau)|tau)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`RMSE(hat(tau)|tau)` <- plots$`RMSE(hat(tau)|tau)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `RMSE(hat(tau)|tau)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(RMSE), "(", hat(tau), "|", tau,
")"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
print(plots$`RMSE(hat(tau)|tau)`)
print(plots$`Bias(hat(tau)|tau)`)
} else {
plots$`Bias(hat(tau)|tau,1)` <- plots$`Bias(hat(tau)|tau,2)` <-
plots$`Bias(hat(tau)|tau)` <- plots$`RMSE(hat(tau)|tau,1)` <-
plots$`RMSE(hat(tau)|tau,2)` <- plots$`RMSE(hat(tau)|tau)` <- NULL
}
##### Outputting #############################################################
if (output) {
return(list(output = output,
plots = plots,
x = x))
}
}
mjg211/OptGS documentation built on May 28, 2021, 3:44 p.m.
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Defines functions plot.OptGS_est
Documented in plot.OptGS_est
#' Plot point estimator performance for two-stage group-sequential clinical
#' trial designs with a normally distributed primary outcome
#'
#' \code{plot.OptGS_est()} plots (conditional and marginal) point estimator bias
#' and residual mean squared error for a specified two-stage group-sequential
#' clinical trial design.
#'
#' @param x An object of class OptGS_est, as returned by \code{\link{est}}.
#' @param ... For compatability with the generic.
#' @param output A \code{\link{logical}} variable indicating whether to return
#' output from the function.
#' @return A \code{\link{list}} containing each of the input variables (subject
#' to internal modification), along with the following elements:
#' \itemize{
#' \item \code{plots}: A \code{\link{list}} containing the available plots.
#' }
#' @examples
#' # For the default two-stage design
#' plot(est(des = opt_gs(), tau = seq(-des$delta, 2*des$delta,
#' length.out = 100)))
#' @seealso \code{\link{est}}
#' @export
plot.OptGS_est <- function(x, ..., output = FALSE) {
##### Input Checking #########################################################
check_OptGS_est(x, "x")
check_logical(output, "output")
##### Main Computations ######################################################
plots <- list()
if (min(x$tau) < 0) {
red <-
tibble::tibble(start = min(x$tau), end = min(0, max(x$tau)))
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
amber <-
tibble::tibble(start = max(0, min(x$tau)),
end = min(x$des$delta, max(x$tau)))
}
if (max(x$tau) > x$des$delta) {
green <-
tibble::tibble(start = max(x$des$delta, min(x$tau)), end = max(x$tau))
}
if (length(unique(x$tau)) > 1) {
plots$`Bias(hat(tau)|tau,1)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`Bias(hat(tau)|tau,1)` <- plots$`Bias(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`Bias(hat(tau)|tau,1)` <- plots$`Bias(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`Bias(hat(tau)|tau,1)` <- plots$`Bias(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`Bias(hat(tau)|tau,1)` <- plots$`Bias(hat(tau)|tau,1)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `Bias(hat(tau)|tau,1)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(Bias), "(", hat(tau), "|", tau,
",1)"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
plots$`Bias(hat(tau)|tau,2)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`Bias(hat(tau)|tau,2)` <- plots$`Bias(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`Bias(hat(tau)|tau,2)` <- plots$`Bias(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`Bias(hat(tau)|tau,2)` <- plots$`Bias(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`Bias(hat(tau)|tau,2)` <- plots$`Bias(hat(tau)|tau,2)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `Bias(hat(tau)|tau,2)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(Bias), "(", hat(tau), "|", tau,
",2)"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
plots$`Bias(hat(tau)|tau)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`Bias(hat(tau)|tau)` <- plots$`Bias(hat(tau)|tau)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`Bias(hat(tau)|tau)` <- plots$`Bias(hat(tau)|tau)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`Bias(hat(tau)|tau)` <- plots$`Bias(hat(tau)|tau)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`Bias(hat(tau)|tau)` <- plots$`Bias(hat(tau)|tau)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `Bias(hat(tau)|tau)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(Bias), "(", hat(tau), "|", tau,
")"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
plots$`RMSE(hat(tau)|tau,1)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`RMSE(hat(tau)|tau,1)` <- plots$`RMSE(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`RMSE(hat(tau)|tau,1)` <- plots$`RMSE(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`RMSE(hat(tau)|tau,1)` <- plots$`RMSE(hat(tau)|tau,1)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`RMSE(hat(tau)|tau,1)` <- plots$`RMSE(hat(tau)|tau,1)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `RMSE(hat(tau)|tau,1)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(RMSE), "(", hat(tau), "|", tau,
",1)"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
plots$`RMSE(hat(tau)|tau,2)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`RMSE(hat(tau)|tau,2)` <- plots$`RMSE(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`RMSE(hat(tau)|tau,2)` <- plots$`RMSE(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`RMSE(hat(tau)|tau,2)` <- plots$`RMSE(hat(tau)|tau,2)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`RMSE(hat(tau)|tau,2)` <- plots$`RMSE(hat(tau)|tau,2)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `RMSE(hat(tau)|tau,2)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(RMSE), "(", hat(tau), "|", tau,
",2)"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
plots$`RMSE(hat(tau)|tau)` <- ggplot2::ggplot() + theme_OptGS()
if (min(x$tau) < 0) {
plots$`RMSE(hat(tau)|tau)` <- plots$`RMSE(hat(tau)|tau)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(x$tau) <= x$des$delta, max(x$tau) >= 0)) {
plots$`RMSE(hat(tau)|tau)` <- plots$`RMSE(hat(tau)|tau)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(x$tau) > x$des$delta) {
plots$`RMSE(hat(tau)|tau)` <- plots$`RMSE(hat(tau)|tau)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plots$`RMSE(hat(tau)|tau)` <- plots$`RMSE(hat(tau)|tau)` +
ggplot2::geom_line(data = x$estimators,
ggplot2::aes(x = tau,
y = `RMSE(hat(tau)|tau)`,
colour = estimator)) +
ggplot2::xlab(expression(tau)) +
ggplot2::ylab(expression(paste(italic(RMSE), "(", hat(tau), "|", tau,
")"))) +
ggplot2::scale_color_manual(values = c("#000000", "#999999", "#E69F00",
"#56B4E9", "#009E73", "#F0E442",
"#0072B2", "#D55E00", "#CC79A7")) +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(x$tau),
max(x$tau)))
print(plots$`RMSE(hat(tau)|tau)`)
print(plots$`Bias(hat(tau)|tau)`)
} else {
plots$`Bias(hat(tau)|tau,1)` <- plots$`Bias(hat(tau)|tau,2)` <-
plots$`Bias(hat(tau)|tau)` <- plots$`RMSE(hat(tau)|tau,1)` <-
plots$`RMSE(hat(tau)|tau,2)` <- plots$`RMSE(hat(tau)|tau)` <- NULL
}
##### Outputting #############################################################
if (output) {
return(list(output = output,
plots = plots,
x = x))
}
}
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