robacf: Robust Autocovariance and Autocorrelation Function Estimation

In robcor: Robust Correlations

Robust Autocovariance and Autocorrelation Function Estimation

Description

Compute (and by default plot) an estimate of the autocovariance or autocorrelation function.

Usage

robacf(x, lag.max = NULL, type = c("correlation", "covariance"), plot = TRUE,
       scaler = "s_FastQn", ...)

Arguments

x	a univariate numeric time series object or a numeric vector.
lag.max	maximum lag at which to calculate the acf. Default is 10*log10(N) where N is the number of observations. Will be automatically limited to one less than the number of observations in the series.
type	character string giving the type of acf to be computed. Allowed values are "correlation" (the default) or "covariance".
plot	logical. If TRUE (the default) the acf is plotted.
scaler	location-scale estimator to use in the algorithm. By default, s_FastQn() is used.
...	further arguments to be passed to plot.acf.

Details

This function is a robust replacement for acf().

Note, that implementation and documentation is not finished/polished yet.

Value

A list of class "acf". For description of elements see acf().

Note

WORK-IN-PROGRESS status.

Author(s)

Paul Smirnov <[e-mail]>

References

Shevlyakov, G. L., Lyubomishchenko, N. S. and Smirnov, P. O. (2013). Some remarks on robust estimation of power spectra. Proceedings of the 11th International Conference on Computer Data Analysis and Modeling, Minsk, Belarus, 97–104.

robcor documentation built on June 27, 2022, 9:06 a.m.