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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