Plot prior distribution(s)

Usage

plot_prior(
  x,
  param = NULL,
  facets = FALSE,
  file = NULL,
  replicates = 10000,
  geom = ggplot2::geom_density,
  ...
)

Arguments

x: Either an object of the class demografr_abc, or a list of prior sampling statements
param: A character vector containing either parameter names to summarize, or a regex-like matches to be used for subsetting. If NULL (the default), all parameters will be extracted.
facets: Should individual parameters be plotting on a facet each?
file: Output file for a figure saved via ggsave
replicates: How many samples to simulate from each prior for plotting?
geom: Either ggplot2::geom_histogram or ggplot2::geom_density
...: Optional argument which will be passed to ggsave

Value

A ggplot2 plot object

Examples

priors <- list(
  Ne_A  ~ runif(1000, 3000),
  Ne_B  ~ runif(100,  1500),
  Ne_C  ~ runif(5000, 10000),
  Ne_D  ~ runif(2000, 7000),

  T_AB  ~ runif(1,    4000),
  T_BC  ~ runif(3000, 9000),
  T_CD  ~ runif(5000, 10000),

  gf_BC ~ runif(0, 0.3)
)

# as with many other distribution plotting functions, plotting everything
# at once doesn't make much sense
# plot_prior(priors)

# it's better to visualize together distributions of the same scale
# plot_prior(priors, "^Ne")
plot_prior(priors, "gf") + ggplot2::xlim(0, 1)