BayesTools (version 0.2.18)

plot.prior: Plots a prior object

Description

Plots a prior object

Usage

# S3 method for prior
plot(
  x,
  plot_type = "base",
  x_seq = NULL,
  xlim = NULL,
  x_range_quant = NULL,
  n_points = 1000,
  n_samples = 10000,
  force_samples = FALSE,
  transformation = NULL,
  transformation_arguments = NULL,
  transformation_settings = FALSE,
  show_figures = if (individual) -1 else NULL,
  individual = FALSE,
  rescale_x = FALSE,
  par_name = NULL,
  ...
)

Value

plot.prior returns either NULL or an object of class 'ggplot' if plot_type is plot_type = "ggplot".

Arguments

x

a prior

plot_type

whether to use a base plot "base" or ggplot2 "ggplot" for plotting.

x_seq

sequence of x coordinates

xlim

x plotting range

x_range_quant

quantile used for automatically obtaining x_range if both x_range and x_seq are unspecified. Defaults to 0.005 for all but Cauchy, Student-t, Gamma, and Inverse-gamme distributions that use 0.010.

n_points

number of equally spaced points in the x_range if x_seq is unspecified

n_samples

number of samples from the prior distribution if the density cannot be obtained analytically (or if samples are forced with force_samples = TRUE)

force_samples

should prior be sampled instead of obtaining analytic solution whenever possible

transformation

transformation to be applied to the prior distribution. Either a character specifying one of the prepared transformations:

lin

linear transformation in form of a + b*x

tanh

also known as Fisher's z transformation

exp

exponential transformation

, or a list containing the transformation function fun, inverse transformation function inv, and the Jacobian of the transformation jac. See examples for details.

transformation_arguments

a list with named arguments for the transformation

transformation_settings

boolean indicating whether the settings the x_seq or x_range was specified on the transformed support

show_figures

which figures should be returned in case of multiple plots are generated. Useful when priors for the omega parameter are plotted and individual = TRUE.

individual

should individual densities be returned (e.g., in case of weightfunction)

rescale_x

allows to rescale x-axis in case a weightfunction is plotted.

par_name

a type of parameter for which the prior is specified. Only relevant if the prior corresponds to a mu parameter that needs to be transformed.

...

additional arguments

See Also

prior() lines.prior() geom_prior()

Examples

# create some prior distributions
p0 <- prior(distribution = "point",  parameters = list(location = 0))
p1 <- prior(distribution = "normal", parameters = list(mean = 0, sd = 1))
p2 <- prior(distribution = "normal", parameters = list(mean = 0, sd = 1), truncation = list(0, Inf))

# a default plot
plot(p0)

# manipulate line thickness and color, change the parameter name
plot(p1, lwd = 2, col = "blue", par_name = bquote(mu))

# use ggplot
plot(p2, plot_type = "ggplot")

# utilize the ggplot prior geom
plot(p2, plot_type = "ggplot", xlim = c(-2, 2)) + geom_prior(p1, col = "red", lty = 2)

# apply transformation
plot(p1, transformation = "exp")