Description Details Slots References See Also

`KernelWeight`

is an S4 class that implements a weighting function by
specification of a kernel function `W`

and a scale parameter `bw`

.

It extends the class `Weight`

and writes

*W_N(2π (k-1)/N) := ∑_{j \in Z} bw^{-1} W(2π 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
*W_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

*W_N^j := ∑_{j \neq s = 0}^{N-1} W_n(2π s / N)*

is stored to `Wnj[s]`

for `s=1,...,N`

, for later usage.

`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.

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

Examples for implementations of kernels `W`

can be found at:
`kernels`

.

quantspec documentation built on May 29, 2017, 3:34 p.m.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.