Recompute Covariance Estimate for fracdiff
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 |
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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