KernelWeight-class function

Class for Brillinger-type Kernel weights.

Class for Brillinger-type Kernel weights.

KernelWeight is an S4 class that implements a weighting function by specification of a kernel function W and a scale parameter bw. class

Details

It extends the class Weight and writes

WN(2π(k1)/N):=jZbw1W(2πbw1[(k1)/N+j]) W_N(2\pi (k-1)/N) := \sum_{j \in Z} bw^{-1} W(2\pi bw^{-1} [(k-1)/N + j])

to values[k] [nested inside env] for k=1,...,N. The number length(values) of Fourier frequencies for which WNW_N will be evaluated may be set on construction or updated when evoking the method getValues. To standardize the weights used in the convolution to unity

WNj:=js=0N1Wn(2πs/N) W_N^j := \sum_{j \neq s = 0}^{N-1} W_n(2\pi s / N)

is stored to Wnj[s] for s=1,...,N, for later usage.

Slots

  • W: a kernel function

  • bw: bandwidth

  • env: An environment to allow for slots which need to be accessable in a call-by-reference manner:

     - **`values`**: A vector storing the weights; see the Details section.
     - **`Wnj`**: A vector storing the terms used for normalization; see the Details section.
    

References

Brillinger, D. R. (1975). Time Series: Data Analysis and Theory. Holt, Rinehart and Winston, Inc., New York. [cf. p. 146 f.]

See Also

Examples for implementations of kernels W can be found at: kernels.

  • Maintainer: Tobias Kley
  • License: GPL (>= 2)
  • Last published: 2024-07-11