TS_acr: Autocovariances and autocorrelations the old-fashioned way.

Description Usage Arguments Value

View source: R/TS_acr.R


This function use the "old-fashioned" way to compute the autocorrelations for a given time series, i.e. the summation-approach. This is much slower than the fast Fourier transform approach used by acf, but it seems more natural to use this when computing the ordinary spectral density in the old fashioned way (using window-functions instead of periodograms).


TS_acr(.TS_info, lag_max = quote(ceiling(3 * sqrt(length(TS)))))



A list containing the three components TS, main_dir and save_dir.


The number of lags to include in the analysis. The default value ceiling(3*sqrt(length(TS))) will probably in most cases include more lags than actually required. It might thus be worthwhile to run some test and see if a smaller value can be used instead.


A file will be created containing an array with the (ordinary) autocorrelations of TS. If save_dir is NULL, then the array will be returned to the workflow directly, otherwise it will be saved to disk.

LAJordanger/localgaussSpec documentation built on July 28, 2017, 12:15 a.m.