Plots  R Documentation 
Visual posterior analysis using ggplot2.
stan_plot(object, pars, include = TRUE, unconstrain = FALSE, ...) stan_trace(object, pars, include = TRUE, unconstrain = FALSE, inc_warmup = FALSE, nrow = NULL, ncol = NULL, ..., window = NULL) stan_scat(object, pars, unconstrain = FALSE, inc_warmup = FALSE, nrow = NULL, ncol = NULL, ...) stan_hist(object, pars, include = TRUE, unconstrain = FALSE, inc_warmup = FALSE, nrow = NULL, ncol = NULL, ...) stan_dens(object, pars, include = TRUE, unconstrain = FALSE, inc_warmup = FALSE, nrow = NULL, ncol = NULL, ..., separate_chains = FALSE) stan_ac(object, pars, include = TRUE, unconstrain = FALSE, inc_warmup = FALSE, nrow = NULL, ncol = NULL, ..., separate_chains = FALSE, lags = 25, partial = FALSE) quietgg(gg)
object 
A stanfit or stanreg object. 
pars 
Optional character vector of parameter names.
If 
include 
Should the parameters given by the 
unconstrain 
Should parameters be plotted on the unconstrained space?
Defaults to 
inc_warmup 
Should warmup iterations be included? Defaults to

nrow,ncol 
Passed to 
... 
Optional additional named arguments passed to geoms
(e.g. for 
window 
For 
separate_chains 
For 
lags 
For 
partial 
For 
gg 
A ggplot object or an expression that creates one. 
For stan_plot
, there are additional arguments that can be specified in
...
. The optional arguments and their default values are:
point_est = "median"
The point estimate to show. Either "median" or "mean".
show_density = FALSE
Should kernel density estimates be plotted above the intervals?
ci_level = 0.8
The posterior uncertainty interval to highlight.
Central 100*ci_level
% intervals are computed from the quantiles of
the posterior draws.
outer_level = 0.95
An outer interval to also draw as a line
(if show_outer_line
is TRUE
) but not highlight.
show_outer_line = TRUE
Should the outer_level
interval
be shown or hidden? Defaults to = TRUE
(to plot it).
fill_color
, outline_color
, est_color
Colors to override the defaults for the highlighted interval, the outer interval (and density outline), and the point estimate.
A ggplot
object that can be further customized
using the ggplot2 package.
Because the rstan plotting functions use ggplot2 (and thus the
resulting plots behave like ggplot
objects), when calling a plotting
function within a loop or when assigning a plot to a name
(e.g., graph < plot(fit, plotfun = "rhat")
),
if you also want the side effect of the plot being displayed you
must explicity print it (e.g., (graph < plot(fit, plotfun = "rhat"))
,
print(graph < plot(fit, plotfun = "rhat"))
).
List of RStan plotting functions
,
Plot options
## Not run: example("read_stan_csv") stan_plot(fit) stan_trace(fit) library(gridExtra) fit < stan_demo("eight_schools") stan_plot(fit) stan_plot(fit, point_est = "mean", show_density = TRUE, fill_color = "maroon") # histograms stan_hist(fit) # suppress ggplot2 messages about default bindwidth quietgg(stan_hist(fit)) quietgg(h < stan_hist(fit, pars = "theta", binwidth = 5)) # juxtapose histograms of tau and unconstrained tau tau < stan_hist(fit, pars = "tau") tau_unc < stan_hist(fit, pars = "tau", unconstrain = TRUE) + xlab("tau unconstrained") grid.arrange(tau, tau_unc) # kernel density estimates stan_dens(fit) (dens < stan_dens(fit, fill = "skyblue", )) dens < dens + ggtitle("Kernel Density Estimates\n") + xlab("") dens (dens_sep < stan_dens(fit, separate_chains = TRUE, alpha = 0.3)) dens_sep + scale_fill_manual(values = c("red", "blue", "green", "black")) (dens_sep_stack < stan_dens(fit, pars = "theta", alpha = 0.5, separate_chains = TRUE, position = "stack")) # traceplot trace < stan_trace(fit) trace + scale_color_manual(values = c("red", "blue", "green", "black")) trace + scale_color_brewer(type = "div") + theme(legend.position = "none") facet_style < theme(strip.background = ggplot2::element_rect(fill = "white"), strip.text = ggplot2::element_text(size = 13, color = "black")) (trace < trace + facet_style) # scatterplot (mu_vs_tau < stan_scat(fit, pars = c("mu", "tau"), color = "blue", size = 4)) mu_vs_tau + ggplot2::coord_flip() + theme(panel.background = ggplot2::element_rect(fill = "black")) ## End(Not run)
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