rejection_plot(p,
col, lty = 1, lwd = 1,
xlab = "p cutoff", ylab = "number of rejections",
xlim = c(0, 1), ylim,
legend = names(p),
at = c("all", "sample"),
n_at = 100,
probability = FALSE,
...
)
NA
entries will be
dropped. If column or element names are supplied, they are used by
default for a plot legend.col
is omitted, rainbow
is used to generate a
set of colors.p
above) are used by default. If NULL
, no legend is
plotted.p
, or should linear interpolation be used at a sample of
points spanning xlim
? The latter looks when there are many
p-values.at = "sample"
is given, how many sample points should be
used for interpolation and plotting?probability
argument to
hist
.# See the vignette: Diagnostic plots for independent filtering
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