simulate.tsissm.estimate {tsissm} | R Documentation |
Model Simulation
Description
Simulation function for class “tsissm.estimate”.
Usage
## S3 method for class 'tsissm.estimate'
simulate(
object,
nsim = 1,
seed = NULL,
h = 1,
newxreg = NULL,
sim_dates = NULL,
bootstrap = FALSE,
innov = NULL,
innov_type = "q",
pars = coef(object),
init_states = tail(object$model$states, 1),
init_res = NULL,
init_sigma = NULL,
...
)
## S3 method for class 'tsissm.selection'
simulate(
object,
nsim = 1,
seed = NULL,
h = 1,
newxreg = NULL,
sim_dates = NULL,
bootstrap = FALSE,
pars = coef(object),
init_states = tail(object$model$states, 1),
init_res = NULL,
init_sigma = NULL,
...
)
Arguments
object |
an object of class “tsissm.estimate”. |
nsim |
the number of paths per complete set of time steps (h). |
seed |
a value specifying if and how the random number generator should be initialized (‘seeded’). Either NULL or an integer that will be used in a call to set.seed before simulating the response vectors. |
h |
the number of time steps to simulate paths for. If this is NULL, it will use the same number of periods as in the original series. |
newxreg |
an optional matrix of regressors to use for the simulation if xreg was used in the estimation. If NULL and the estimated object had regressors, and h was also set to NULL, then the original regressors will be used. |
sim_dates |
an optional vector of simulation dates equal to h. If NULL will use the implied periodicity of the data to generate a regular sequence of dates after the first available date in the data. |
bootstrap |
whether to bootstrap the innovations from the estimated object by re-sampling from the empirical distribution. |
innov |
an optional vector of innovations (see innov_type). The length of this vector should be equal to nsim x horizon. |
innov_type |
if ‘innov’ is not NULL, then this denotes the type of values passed, with “q” denoting quantile probabilities (default and backwards compatible) and “z” for standardized errors. |
pars |
an optional named vector of model coefficients which override the estimated coefficients. No checking is currently performed on the adequacy of these coefficients. |
init_states |
An optional vector of states to initialize the forecast. If NULL, will use the first available states from the estimated model. |
init_res |
For a dynamic variance model, the initialization for the ARCH recursion of length equal to max(p,q). |
init_sigma |
For a dynamic variance model, the standard deviation initialization for the GARCH recursion of length equal to max(p,q). |
... |
not currently used. |
Value
An object of class “tsissm.simulate” with slots for the simulated series and states.