fracdiff (version 1.5-1)

fracdiff.var: Recompute Covariance Estimate for fracdiff

Description

Allows the finite-difference interval to be altered for recomputation of the covariance estimate for fracdiff.

Usage

fracdiff.var(x, fracdiff.out, h)

Value

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.

Arguments

x

a univariate time series or a vector. Missing values (NAs) are not allowed.

fracdiff.out

output from fracdiff for time series x.

h

finite-difference interval for approximating partial derivatives with respect to the d parameter.

See Also

fracdiff, also for references.

Examples

## 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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