R: Covariance Generation

covgen {timsac} | R Documentation

## Covariance Generation

### Description

Produce the Fourier transform of a power gain function in the form of an autocovariance sequence.

### Usage

      covgen(lag, f, gain, plot=TRUE)

### Arguments

`lag` | desired maximum lag of covariance.
`f` | frequency `f(i)` (i=1,...,k), where k is the number of data points. By definition `f(1)` = 0.0 and `f(k)` = 0.5, `f(i)`'s are arranged in increasing order.
`gain` | power gain of the filter at the frequency `f(i)`.
`plot` | logical. If TRUE (default) autocorrelations are plotted.

### Value

`acov` | autocovariance.
`acor` | autocovariance normalized.

### References

H.Akaike, E.Arahata and T.Ozaki (1975) Computer Science Monograph, No.5, Timsac74, A Time Series Analysis and Control Program Package (1). The Institute of Statistical Mathematics.

### Examples

      spec <- raspec(h=100, var=1, arcoef=c(0.64,-0.8), plot=FALSE)
      covgen(lag=100, f=0:100/200, gain=spec)

[Package timsac version 1.3.5 Index]