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)
``` |

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