robacf:
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.
Value
A list of class "acf". For description of elements see acf().
Details
This function is a robust replacement for acf().Note, that implementation and documentation is not finished/polished yet.
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.