Plot samples from the mixed posterior distributions

plot_posterior(
samples,
parameter,
plot_type = "base",
prior = FALSE,
n_points = 1000,
n_samples = 10000,
force_samples = FALSE,
transformation = NULL,
transformation_arguments = NULL,
transformation_settings = FALSE,
rescale_x = FALSE,
par_name = NULL,
dots_prior = list(),
...
)

## Arguments

samples samples from a posterior distribution for a parameter generated by mix_posteriors. parameter name to be plotted. Use "PETPEESE" for PET-PEESE plot with parameters "PET" and "PEESE", and "weightfunction" for plotting a weightfunction with parameters "omega". whether to use a base plot "base" or ggplot2 "ggplot" for plotting. whether prior distribution should be added to the figure number of equally spaced points in the x_range if x_seq is unspecified number of samples from the prior distribution if the density cannot be obtained analytically (or if samples are forced with force_samples = TRUE) should prior be sampled instead of obtaining analytic solution whenever possible transformation to be applied to the prior distribution. Either a character specifying one of the prepared transformations: linlinear transformation in form of a + b*x tanhalso known as Fisher's z transformation expexponential transformation , or a list containing the transformation function fun, inverse transformation function inv, and the Jacobian of the transformation jac. See examples for details. a list with named arguments for the transformation boolean indicating whether the settings the x_seq or x_range was specified on the transformed support allows to rescale x-axis in case a weightfunction is plotted. 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 for the prior distribution plot additional arguments

## Value

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

prior() lines_prior_list() geom_prior_list()