| fracdiff.var | R Documentation |
Allows the finite-difference interval to be altered for recomputation of the
covariance estimate for fracdiff.
fracdiff.var(x, fracdiff.out, h)
x |
a univariate time series or a vector. Missing values (NAs) are not allowed. |
fracdiff.out |
output from |
h |
finite-difference interval for approximating partial
derivatives with respect to the |
an object of S3 class "fracdiff", i.e., basically
a list with the same elements as the result from
fracdiff, but with possibly different values for the
hessian, covariance, and correlation matrices and for standard error,
as well as for h.
fracdiff, also for references.
## 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 series
fd.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)
## A case, were the default variance is *clearly* way too small:
set.seed(1); fdc <- fracdiff(X <- fracdiff.sim(n=100,d=0.25)$series)
fdc
# Confidence intervals just based on asymp.normal approx. and std.errors:
confint(fdc) # ridiculously too narrow
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