plot.gg_brier: Plot a `gg_brier` object

Description

Draws the time-resolved Brier score or the running CRPS from a gg_brier object. The curve moves across the event-time grid on the x-axis; lower values mean the forest's predicted survival probabilities are closer to what actually happened. Think of 0 as "perfect" and roughly 0.25 as "uninformative" -- a forest that predicts 0.5 for every subject regardless of prognosis would sit near that ceiling.

Usage

# S3 method for gg_brier
plot(x, type = c("brier", "crps"), envelope = FALSE, ...)

Value

A ggplot object.

Arguments

x: A gg_brier object.
type: Which series to plot: "brier" (default) or "crps".
envelope: Logical. When TRUE, overlays a ribbon spanning the 15th-85th percentile of per-subject Brier (or running CRPS) contributions at each time, around the overall line. When FALSE (default), draws the overall series only.
...: Extra arguments forwarded to geom_line().

Details

Set envelope = TRUE to add a ribbon around the overall curve spanning the 15th to 85th percentile of the per-subject Brier contributions at each time. The ribbon shows how heterogeneous the scoring is across subjects: a narrow ribbon means most subjects are predicted equally well (or equally poorly); a wide ribbon means a minority of subjects are driving the average.

Examples

Run this code

# \donttest{
library(survival)   # Surv() must be on the search path for rfsrc()
data(pbc, package = "randomForestSRC")
rf <- randomForestSRC::rfsrc(Surv(days, status) ~ ., data = pbc,
                             nsplit = 10)
gg_dta <- gg_brier(rf)
plot(gg_dta)
plot(gg_dta, type = "crps")
plot(gg_dta, envelope = TRUE)   # adds 15-85% envelope
# }