Plot Prior Objects

Plot prior distributions as densities. Continuous distributions are plotted as curves and discrete distributions as bar plots.

Usage

# S4 method for Prior,missing
plot(
  x,
  y,
  default_limits,
  dist_type = c("continuous", "discrete"),
  density_fun,
  add,
  ...
)

# S4 method for NormalPrior,missing
plot(x, y, add = FALSE, ...)

# S4 method for BernoulliPrior,missing
plot(x, y, add = FALSE, ...)

# S4 method for BetaPrior,missing
plot(x, y, add = FALSE, ...)

# S4 method for CauchyPrior,missing
plot(x, y, add = FALSE, ...)

# S4 method for ExponentialPrior,missing
plot(x, y, add = FALSE, ...)

# S4 method for GammaPrior,missing
plot(x, y, add = FALSE, ...)

# S4 method for HalfCauchyPrior,missing
plot(x, y, add = FALSE, ...)

# S4 method for HalfNormalPrior,missing
plot(x, y, add = FALSE, ...)

# S4 method for PoissonPrior,missing
plot(x, y, add = FALSE, ...)

# S4 method for UniformPrior,missing
plot(x, y, add = FALSE, ...)

Arguments

x

Object inheriting from Prior

y

Not used.

default_limits

Numeric range to plot distribution over.

dist_type

Plot a continuous or discrete distribution.

density_fun

Function which takes a vector of values and returns a vector of density values.

add

logical. Add density to existing plot.

...

Optional arguments for plotting.

Details

Plot ranges are selected by default to show 99% of the density for unbounded distributions. The limits can be changed by specifying xlim = c(lower, upper).

Colors, line types, and other typical par() parameters can be used.

Examples

plot(normal_prior(1, 2))

plot(bernoulli_prior(0.4), xlim = c(0, 15))

plot(beta_prior(2, 2))

plot(cauchy_prior(0, 1), xlim = c(-20, 20))
plot(cauchy_prior(0, 2), xlim = c(-20, 20), col = 2, add = TRUE)

plot(exponential_prior(0.1))

plot(gamma_prior(0.1, 0.1))

plot(half_cauchy_prior(0, 1), xlim = c(-20, 20))
plot(half_cauchy_prior(0, 2), xlim = c(-20, 20), col = 2, add = TRUE)

plot(half_normal_prior(0, 1), xlim = c(-20, 20))
plot(half_normal_prior(0, 2), xlim = c(-20, 20), col = 2, add = TRUE)

plot(poisson_prior(5), xlim = c(0, 15))

plot(uniform_prior(1, 2), xlim = c(0, 3))