| plot.bartcs {bartcs} | R Documentation |
Draw plot for bartcs object
Description
Two options are available: posterior inclusion probability (PIP) plot and trace plot.
Usage
## S3 method for class 'bartcs'
plot(x, method = NULL, parameter = NULL, ...)
Arguments
x |
A |
method |
" |
parameter |
Parameter for traceplot. |
... |
Additional arguments for PIP plot.
Check |
Details
PIP plot
When a posterior sample is sampled during training,
separate_bart() or single_bart() also counts
which variables are included in the model and
compute PIP for each variable.
For bartcs object x,
this is stored in x$var_count and x$var_prob respectively.
plot(method = "pip") uses this information and
draws plot using ggcharts::bar_chart().
Traceplot
Parameters are recorded for each MCMC iterations.
Parameters include "ATE", "Y1", "Y0", "dir_alpha",
and either "sigma2_out" from single_bart()
or "sigma2_out1" and "sigma2_out0" from
separate_bart().
Vertical line indicates burn-in.
Value
A ggplot object of either PIP plot or trace plot.
Examples
data(ihdp, package = "bartcs")
x <- single_bart(
Y = ihdp$y_factual,
trt = ihdp$treatment,
X = ihdp[, 6:30],
num_tree = 10,
num_chain = 2,
num_post_sample = 20,
num_burn_in = 10,
verbose = FALSE
)
# PIP plot
plot(x, method = "pip")
plot(x, method = "pip", top_n = 10)
plot(x, method = "pip", threshold = 0.5)
# Check `?ggcharts::bar_chart` for other possible arguments.
# trace plot
plot(x, method = "trace")
plot(x, method = "trace", "Y1")
plot(x, method = "trace", "dir_alpha")