This method minimizes an approximate log-likelihood function (applied to
the spectral density) to obtain an estimate of the parameters of a process.
It is parametric and does not produce a graphical output.
A more detailed description.
There are several options for using the Whittle estimator. Some are
- The data is here called xinput.
- One can optionally subdivide the series into subseries
(nsub, default is 1).
- One can output the periodogram (spec, default = NO).
- One can ouput intermediate minimization results (out,
default = YES).
- The model can be either "farima" or "fgn".
- If it is "farima", pp and qq set the order of the
autoregressive and moving average parts respectively.
- h is the starting value of H for the minimization
- ar and ma are the vectors corresponding to the
starting values of the other parameters. (Length of vectors should be the
same as pp and qq.
- To use the Aggregated Whittle method, first aggregate the data, and
then use the FGN model in the Whittle estimator.