arima.boot {TSA} | R Documentation |
This function bootstraps time series according to the fitted ARMA(p,d,q) model supplied by the fitted object arima.fit, and estimate the same model using the arima function.
arima.boot(arima.fit, cond.boot = FALSE, is.normal = TRUE, B = 1000, init, ntrans = 100)
arima.fit |
a fitted object from the arima function (seasonal components not allowed) |
cond.boot |
whether or not the bootstrap is conditional on the (p+d) initial values; if it is set true. If false (default), the stationary bootstrap is used. |
is.normal |
if true (default), errors are normally distributed, otherwise errors are drawn randomly and with replacement from the residuals of the fitted model. |
B |
number of bootstrap replicates (1000, default) |
init |
initial values for the bootstrap; needed if cond.boot=True default values are the initial values of the time series of the fitted model. |
ntrans |
number of transient values for the stationary bootstrap. Default=100 |
a matrix each row of which consists of the coefficient estimates of a bootstrap time-series.
Kung-Sik Chan
data(hare) arima.hare=arima(sqrt(hare),order=c(3,0,0)) boot.hare=arima.boot(arima.hare,B=50,init=sqrt(hare)[1:3],ntrans=100) apply(boot.hare,2,quantile, c(.025,.975)) period.boot=apply(boot.hare,1,function(x){ roots=polyroot(c(1,-x[1:3])) min1=1.e+9 rootc=NA for (root in roots) { if( abs(Im(root))<1e-10) next if (Mod(root)< min1) {min1=Mod(root); rootc=root} } if(is.na(rootc)) period=NA else period=2*pi/abs(Arg(rootc)) period }) hist(period.boot) quantile(period.boot,c(0.025,.975))