kDGLM (version 1.2.0)

update.fitted_dlm: update.fitted_dlm

Description

update.fitted_dlm

Usage

# S3 method for fitted_dlm
update(object, ...)

Value

A fitted_dlm object.

Arguments

object

fitted_dlm: The fitted model to be updated.

...

Extra variables necessary for updating (covariates, observed values, etc.).

Details

If an a covariate is necessary for updating, it should be passed as a named argument. Its name must follow this structure: <block name>.Covariate<.index>. If there is only one pulse in the associated block the index is omitted. If an a pulse is necessary for updating, it should be passed as a named argument. Its name must follow this structure: <block name>.Pulse<.index>. If there is only one pulse in the associated block the index is omitted. If an offset is necessary for updating, it should be passed along with the observed data. See example.

See Also

Other auxiliary functions for fitted_dlm objects: coef.fitted_dlm(), eval_dlm_norm_const(), fit_model(), forecast.fitted_dlm(), simulate.fitted_dlm(), smoothing()

Examples

level <- polynomial_block(rate = 1, order = 2, D = 0.95)
season <- harmonic_block(rate = 1, order = 2, period = 12, D = 0.975)

# Only first 100 observations (for the sake of the example)
outcome <- Poisson(lambda = "rate", data = c(AirPassengers)[1:100])

fitted.data <- fit_model(level, season,
  AirPassengers = outcome
)

updated.fit <- update(fitted.data, AirPassengers = list(data = c(AirPassengers)[101:144]))
# If a offset was present, the user should pass its value when updating
# updated.fit=update(fitted.data,
#                     AirPassengers=list(
#                      data=c(AirPassengers)[101:144],
#                      offset= ... ))