Description Usage Arguments Details Value Author(s) Examples
Plot prior or posterior model draws on top of data. Use plot_pars
to
plot individual parameter estimates.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 
x 
An 
facet_by 
String. Name of a varying group. 
lines 
Positive integer or 
geom_data 
String. One of "point" (default), "line" (good for timeseries), or FALSE (don not plot). 
cp_dens 
TRUE/FALSE. Plot posterior densities of the change point(s)?
Currently does not respect 
q_fit 
Whether to plot quantiles of the posterior (fitted value).

q_predict 
Same as 
rate 
Boolean. For binomial models, plot on raw data ( 
prior 
TRUE/FALSE. Plot using prior samples? Useful for 
which_y 
What to plot on the yaxis. One of

arma 
Whether to include autoregressive effects.

nsamples 
Integer or 
scale 
One of

... 
Currently ignored. 
plot()
uses fit$simulate()
on posterior samples. These represent the
(joint) posterior distribution.
A ggplot2 object.
Jonas Kristoffer Lindeløv jonas@lindeloev.dk
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15  # Typical usage. ex_fit is an mcpfit object.
plot(ex_fit)
plot(ex_fit, prior = TRUE) # The prior
plot(ex_fit, lines = 0, q_fit = TRUE) # 95% HDI without lines
plot(ex_fit, q_predict = c(0.1, 0.9)) # 80% prediction interval
plot(ex_fit, which_y = "sigma", lines = 100) # The variance parameter on y
# Show a panel for each varying effect
# plot(fit, facet_by = "my_column")
# Customize plots using regular ggplot2
library(ggplot2)
plot(ex_fit) + theme_bw(15) + ggtitle("Great plot!")

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