Given one or more fitted ebnm
object(s), produces a plot of
posterior means vs. observations. If desired, a plot of cumulative
distribution functions of fitted prior(s) can also be produced.
# S3 method for ebnm
plot(
x,
...,
incl_pm = TRUE,
incl_cdf = FALSE,
subset = NULL,
remove_abline = FALSE
)
The fitted ebnm
object.
Additional ebnm
objects to be included on the same plots.
Plot posterior means vs. observations?
Plot the cumulative distribution functions?
The subset of observations to include on the plot of posterior
means vs. observations. Can be a numeric vector corresponding to indices
of observations to plot, or a character vector if observations are named.
If subset = NULL
then all observations will be plotted.
To better illustrate shrinkage effects, the plot of
posterior means vs. observations includes the line \(y = x\) by default.
If remove_abline = TRUE
, then this line will not be drawn.
theta <- c(rep(0, 100), rexp(100))
theta[1:50] <- 0
s <- 1
x <- theta + rnorm(200, 0, s)
pn.res <- ebnm_point_normal(x, s)
plot(pn.res)
pe.res <- ebnm_point_exponential(x, s)
plot(pn.res, pe.res)
# Customize plot:
library(ggplot2)
plot(pn.res, pe.res, remove_abline = TRUE) +
theme_bw() +
labs(x = "Simulated data")