nse.boot {nse}

Bootstrap estimator

Description

Function which calculates the numerical standard error with bootstrap estimator.

Usage

nse.boot(x, nb, type = c("stationary", "circular"), b = NULL, lag.prewhite = 0)

Arguments

x

A numeric vector.

nb

The number of bootstrap replications.

type

The bootstrap scheme used, among "stationary" and "circular". Default is type = "stationary".

b

The block length for the block bootstrap. If NULL automatic block length selection. Default is b = NULL.

lag.prewhite

Prewhite the series before analysis (integer or NULL). When lag.prewhite = NULL this performs automatic lag selection. Default is lag.prewhite = 0 that is no prewhitening.

Value

The NSE estimator.

Note

nse.boot uses b.star of the np package for the optimal block length selection.

Author(s)

David Ardia and Keven Bluteau

References

Politis, D.N., Romano, and J.P. (1992). A circular block-resampling procedure for stationary data. In Exploring the limits of bootstrap, John Wiley & Sons, 263-270.

Politis, D.N., Romano, and J.P. (1994). The stationary bootstrap. Journal of the American Statistical Association 89(428), 1303-1313.

Politis, D.N., White, H. (2004). Automatic block-length selection for the dependent bootstrap. Econometric Reviews 23(1), 53-70.

Examples

## Not run: 
n    = 1000
ar   = 0.9
mean = 1
sd   = 1

set.seed(1234)
x = c(arima.sim(n = n, list(ar = ar), sd = sd) + mean)

set.seed(1234)
nse.boot(x = x, nb = 1000, type = "stationary", b = NULL, lag.prewhite = 0)
nse.boot(x = x, nb = 1000, type = "circular", b = NULL, lag.prewhite = NULL)
nse.boot(x = x, nb = 1000, type = "circular", b = 10, lag.prewhite = NULL)

## End(Not run)