mvgam
objectExtract hindcasts for a fitted mvgam
object
hindcast(object, ...)# S3 method for mvgam
hindcast(object, type = "response", ...)
An object of class mvgam_forecast
containing hindcast distributions.
See mvgam_forecast-class
for details.
list
object of class mvgam
or jsdgam
. See mvgam()
Ignored
When this has the value link
(default) the linear predictor is
calculated on the link scale.
If expected
is used, predictions reflect the expectation of the response (the mean)
but ignore uncertainty in the observation process. When response
is used,
the predictions take uncertainty in the observation process into account to return
predictions on the outcome scale. When variance
is used, the variance of the response
with respect to the mean (mean-variance relationship) is returned.
When type = "terms"
, each component of the linear predictor is
returned separately in the form of a list
(possibly with standard
errors, if summary = TRUE
): this includes parametric model components,
followed by each smooth component, but excludes any offset and any intercept.
Two special cases are also allowed:
type latent_N
will return the estimated latent abundances from an
N-mixture distribution, while type detection
will return the estimated
detection probability from an N-mixture distribution
Posterior retrodictions are drawn from the fitted mvgam
and
organized into a convenient format
forecast.mvgam
# \donttest{
simdat <- sim_mvgam(n_series = 3, trend_model = AR())
mod <- mvgam(y ~ s(season, bs = 'cc'),
trend_model = AR(),
noncentred = TRUE,
data = simdat$data_train,
chains = 2,
silent = 2)
# Hindcasts on response scale
hc <- hindcast(mod)
str(hc)
plot(hc, series = 1)
plot(hc, series = 2)
plot(hc, series = 3)
# Hindcasts as expectations
hc <- hindcast(mod, type = 'expected')
str(hc)
plot(hc, series = 1)
plot(hc, series = 2)
plot(hc, series = 3)
# Estimated latent trends
hc <- hindcast(mod, type = 'trend')
str(hc)
plot(hc, series = 1)
plot(hc, series = 2)
plot(hc, series = 3)
# }
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