View source: R/tidier_methods.R
| augment.mvgam | R Documentation |
mvgam object's dataAdd fits and residuals to the data, implementing the generic augment from
the package broom.
## S3 method for class 'mvgam'
augment(x, robust = FALSE, probs = c(0.025, 0.975), ...)
x |
An object of class |
robust |
If |
probs |
The percentiles to be computed by the quantile function. |
... |
Unused, included for generic consistency only. |
A list is returned if class(x$obs_data) == 'list', otherwise a tibble
is returned, but the contents of either object is the same.
The arguments robust and probs are applied to both the fit and residuals
calls (see fitted.mvgam() and residuals.mvgam() for details).
A list or tibble (see details) combining:
The data supplied to mvgam().
The outcome variable, named as .observed.
The fitted backcasts, along with their variability and credible bounds.
The residuals, along with their variability and credible bounds.
residuals.mvgam,
fitted.mvgam
Other tidiers:
tidy.mvgam()
## Not run:
set.seed(0)
dat <- sim_mvgam(
T = 80,
n_series = 3,
mu = 2,
trend_model = AR(p = 1),
prop_missing = 0.1,
prop_trend = 0.6
)
mod1 <- mvgam(
formula = y ~ s(season, bs = 'cc', k = 6),
data = dat$data_train,
trend_model = AR(),
family = poisson(),
noncentred = TRUE,
chains = 2,
silent = 2
)
augment(mod1, robust = TRUE, probs = c(0.25, 0.75))
## End(Not run)
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