Description Usage Arguments Details Value Author(s) References See Also Examples
The function generates a sieve bootstrap sample for a univariate stochastic process.
1 | sieve.bootstrap(y,reps = 1000,pmax = NULL,h = 100,seed = NULL)
|
y |
a numeric vector or an object of the |
reps |
an integer with the total bootstrap repetitions. |
pmax |
an integer with the max considered lags for the generated |
h |
an integer with the first |
seed |
An optional |
simulates bootstrap samples for the stochastic process y, using a stationary
auto-regressive model of order "pmax"
, AR(pmax)
. If pmax = NULL
(default),
the function estimates the process maximum lags using an AIC
as a model
selection criteria.
A matrix or reps
row and n
columns, with the sieve bootstrap
sample and n
the time series length.
Asael Alonzo Matamoros
Bulmann, P. (1997). Sieve Bootstrap for time series. Bernoulli. 3(2), 123 -148.
1 2 3 | # Generating an stationary arma process
y = arima.sim(100,model = list(ar = 0.3))
M = sieve.bootstrap(y)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.