Computes the binned autocorrelation function of a series of event times.
The data is assumed to represent a sum of delta functions centered at the times given. The autocorrelation function is then a double sum of delta functions which must be binned to be representable. Therfore, you have to choose the duration of a single bin (with argument bin) and the maximum time lag (argument bintot) considered.
Inputs
This function always assumes that each time series is along the longer dimension of matrix S. It also assumes that every dimension (counting along the shorter dimension) of S is considered a component of the time series.
The duration of a single bin.
The maximum lag considered.
Switch
Treat the input as inter-event intervals instead of the time at which the event occured.
Output
The output is alligned with the input. If the input was a column vector the output will consist of two columns, the first holds information about which bin did the autocorellation fit into, and the second the number of autocorellations that fit into that bin.
Algorithms
The algorithms for this functions have been taken from the TISEAN package.
Package: tisean