dfa_loadings {bayesdfa} | R Documentation |
Get the loadings from a DFA as a data frame
dfa_loadings(rotated_modelfit, names = NULL, summary = TRUE, conf_level = 0.95)
rotated_modelfit |
Output from |
names |
An optional vector of names for plotting the loadings. |
summary |
Logical. Should the full posterior densities be returned? Defaults to |
conf_level |
Confidence level for credible intervals. Defaults to 0.95. |
A data frame with the following columns:
name
is an identifier for each loading, trend
is the trend for the
loading, median
is the posterior median loading, lower
is the lower CI,
upper
is the upper CI, and prob_diff0
is the probability the loading is
different than 0. When summary = FALSE
, there is no lower
or upper
columns and instead there are columns chain
and draw
.
plot_loadings fit_dfa rotate_trends
set.seed(42) s <- sim_dfa(num_trends = 2, num_ts = 4, num_years = 10) # only 1 chain and 180 iterations used so example runs quickly: m <- fit_dfa(y = s$y_sim, num_trends = 2, iter = 50, chains = 1) r <- rotate_trends(m) loadings <- dfa_loadings(r, summary = TRUE) loadings <- dfa_loadings(r, summary = FALSE)