For a given time series Y a lag-window estimator of the Form
$$\hat{f}(\omega) = \sum_{|k|< n-1 } K_n(k) \Gamma(Y_0,Y_k) \exp(-i \omega k)$$
will be calculated on initalization. The LagKernelWeight
K_n is determined
by the slot weight
and the LagOperator
\(\Gamma(Y_0,Y_k)\) is defined
by the slot lagOp.
Y
the time series where the lag estimator was applied one
weight
a Weight
object to be used as lag window
lagOp
a LagOperator
object that determines which
kind of bivariate structure should be calculated.
env
An environment to allow for slots which need to be accessable in a call-by-reference manner:
sdNaive
An array used for storage of the naively estimated standard deviations of the smoothed periodogram.
sdNaive.done
a flag indicating whether sdNaive
has been set yet.
Currently, the implementation of this class allows only for the analysis of univariate time series.