plot_mvgam_factors {mvgam} | R Documentation |
Latent factor summaries for a fitted mvgam object
Description
This function takes a fitted mvgam
object and returns plots and summary statistics for
the latent dynamic factors
Usage
plot_mvgam_factors(object, plot = TRUE)
Arguments
object |
|
plot |
|
Details
If the model in object
was estimated using dynamic factors, it is possible that not all factors
contributed to the estimated trends. This is due to the regularisation penalty that acts independently on each
factor's Gaussian precision, which will squeeze un-needed factors to a white noise process (effectively dropping
that factor from the model). In this function, each factor is tested against a null hypothesis of white noise by
calculating the sum of the factor's 2nd derivatives. A factor that has a larger contribution will have a larger
sum due to the weaker penalty on the factor's precision. If
plot == TRUE
, the factors are also plotted.
Value
A dataframe
of factor contributions and,
optionally, a series of base R
plots
Author(s)
Nicholas J Clark
Examples
simdat <- sim_mvgam()
mod <- mvgam(y ~ s(season, bs = 'cc',
k = 6),
trend_model = AR(),
use_lv = TRUE,
n_lv = 2,
data = simdat$data_train,
chains = 2)
plot_mvgam_factors(mod)