Plot a list of prior distributions
plot_prior_list(
prior_list,
plot_type = "base",
x_seq = NULL,
xlim = NULL,
x_range_quant = NULL,
n_points = 500,
n_samples = 10000,
force_samples = FALSE,
individual = FALSE,
show_figures = if (individual) 1 else NULL,
transformation = NULL,
transformation_arguments = NULL,
transformation_settings = FALSE,
rescale_x = FALSE,
par_name = NULL,
prior_list_mu = NULL,
effect_direction = "positive",
legend = TRUE,
legend_title = NULL,
legend_labels = NULL,
legend_position = NULL,
...
)list of prior distributions
whether to use a base plot "base"
or ggplot2 "ggplot" for plotting.
sequence of x coordinates
x plotting range
quantile used for
automatically obtaining x_range
if both x_range and x_seq
are unspecified. A number in the open interval (0, 0.5);
other values are refused. Defaults to 0.005
for all but Cauchy, Student-t, Gamma, inverse-gamma,
moment, and inverse-moment distributions that use
0.010.
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. For supported ordered
mixed measures, exact analytic curves and atoms are retained and the
requested samples are attached to each component. Supported scalar ordered
literal point totals and mixtures whose total components are all literal
points do not sample, store draws, or advance the RNG when
force_samples = FALSE. With force_samples = TRUE, their
original seeded draws are attached without replacing the analytic measure.
Other ordered families retain their existing sampling fallback.
should individual densities be returned (e.g., in case of weightfunction)
which figures should be returned in case of
multiple plots are generated. Useful when priors for the omega
parameter are plotted and individual = TRUE. For weight functions
plotted individually by plot.prior() and plot_posterior(),
figure k shows the publication weight omega of the k-th
p-value interval in ascending order, the order in which summary tables
(including RoBMA's) print the omegas; figure 1 is the reference weight of
the most significant interval. In plot.prior(), a negative k
omits figure -k (the default -1 omits the reference weight
fixed at 1). For a two-sided weight function prior, the intervals are its
two-sided p-value bins; tables on the one-sided p-value scale print these
weights first and then repeat them for the mirrored intervals.
transformation to be applied to the prior distribution. Either a character specifying one of the prepared transformations:
linear transformation in form of a + b*x
hyperbolic tangent transformation
exponential transformation
, or a list containing the transformation function fun,
inverse transformation function inv, and derivative of the
transformation jac, evaluated on the original support. A custom
transformation can also declare output_support = c(lower, upper).
Display grids on the transformed scale are evaluated only within these
bounds; a wider plotting range is retained without extending the density.
Infinite inverse values at support boundaries are omitted from continuous
density grids. Point masses retain their transformed locations.
a list with named arguments for
the transformation
boolean indicating whether the
explicitly supplied x_seq or x_range is on
the transformed scale. Automatically selected prior-coordinate ranges
are always obtained on the source scale before the density family's
existing transformation handling.
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.
list of priors for the mu parameter, required for the
PET-PEESE regression bands (individual = FALSE) and refused otherwise:
an individual plot shows the density of one coefficient and does not use it
direction of the effect for PET-PEESE
regression. Use "positive" (default) for
mu + PET*se + PEESE*se^2 or "negative" for
mu - PET*se - PEESE*se^2.
whether factor legends should be drawn.
optional title for factor legends.
optional labels for factor legend levels.
optional legend position for factor legends.
additional graphical arguments. For mixed continuous and point
distributions, ylim controls the density axis, ylim2 controls
the probability-mass axis, and ylab2 controls its label.
plot_prior_list returns either NULL or
an object of class 'ggplot' if plot_type is plot_type = "ggplot".
Automatic prior-coordinate ranges use a common source grid before
transformation, regardless of transformation_settings. An endpoint
with an infinite image uses the union of participating component marginal tail
quantiles, as described in density.prior(). This display convention keeps
exact atoms, mixture weights and prior support; explicit coordinates retain
their supplied interpretation. The nonindividual PET/PEESE and weightfunction
axes keep their standard-error and p-value meanings.