
Hi,I have a question about the fracdiff.var function (package fracdiff) which goal is to recompute more precise confidence intervals for the parameters estimated by fracdiff (or arfima). More precisely, it deals with the standard error of the "d" coefficient :
Is it normal that the standard error of the "d" coefficient can be brought customly close to zero by decreasing the "h" argument ?
The example of the help file shows this fact :
{Quote}
## Generate a fractionally-differenced ARIMA(1,d,1) model :ts.test <- fracdiff.sim(10000, ar = .2, ma = .4, d = .3)## estimate the parameters in an ARIMA(1,d,1) model for the simulated seriesfd.out <- fracdiff(ts.test$ser, nar= 1, nma = 1)
## Modify the covariance estimate by changing the finite-difference interval(fd.o2 <- fracdiff.var(ts.test$series, fd.out, h = .0001))## looks identical as  print(fd.out),## however these (e.g.) differ :vcov(fd.out)vcov(fd.o2)
{end of quote}
Looking at vcov(fd.o2) gives that sd's are indeed lower than in vcov(fd.out). However, by testing :
vcov(fracdiff.var(ts.test$series, fd.o2, h = 0.00000000001))or evenvcov(fracdiff.var(ts.test$series, fd.o2, h = 1e-90))
the sd of "d" doesn't stop decreasing, while the others have reached their "computational" limit.
Is that normal ? If not, which value of sd(d) can I use ?
Hopping I have been clear enough,Many thanks ! 		 	   		  
	[[alternative HTML version deleted]]

