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return_time may be used to find hidden periodicity in
multivariate data, e.g. embedded time series data. It computes a
histogram of return times. For any given reference
point, return_time calculates the time span until the time series
returns to that location in phase space (by means of nearest
neighbors). A histogram of these time spans is computed. Strong
peaks in this histogram might be a sign of periodicity in the
data.
Syntax:
- r = return_time(pointset, query_indices, k, max_time, exclude)
- r = return_time(atria, pointset, query_indices, k, max_time, exclude)
Input arguments:
- atria - output of nn_prepare for pointset (optional) (cf. Section 6.13)
- pointset - a N by D double matrix
containing the coordinates of the point set, organized as
N points of dimension D
- query_indices - query points are taken out of the
pointset, query_indices is a vector of length R
which contains the indices of the query points (indices
may vary from 1 to N)
- k - number of nearest neighbors to be determined
- max_time - integer scalar, gives an upper limit for
return times that should be considered.
- exclude - in case the query points are taken out of the
pointset, exclude specifies a range of indices which are
omitted from search. For example if the index of the query point
is 124 and exclude is set to 3, points with indices 121
to 127 are omitted from search. Using exclude = 0 means:
exclude self-matches
Output arguments:
- r - vector of length max_time, containing the histogram
of return times
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Up: 6. Mex-Function Reference
Previous: 6.16 range_search
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