Description Usage Arguments Details Value References See Also
Computes the Edit distance on Real Sequence as described by Chen, Özsu
and Oria (2005). A match between two (real-valued) time series elements exists
if their L1 distance is below an epsilon
. Apart from that, the
computation is similar to the standard edit distance. The coding is inspired
by the TSdist::EDRDistance()
method, but faster because point-to-point
distances computation is integrated into the C++ code.
1 | EDRDist_fast(x, y, epsilon, normalize = FALSE)
|
x |
1st numeric vector/time series. |
y |
2nd numeric vector/time series. |
epsilon |
Maximum distance between two time series elements to count a match. |
normalize |
Normalize the result to [0,1] considering the maximum possible dissimilarity. |
Despite the name, it is not really a distance in the strict sense, as EDR violates the triangular inequality.
The distance as double.
Chen, L., Özsu, M. T. & Oria, V. (2005). Robust and fast similarity search for moving object trajectories. In Proceedings of the 2005 acm sigmod international conference on management of data (pp. 491–502). ACM.
Other Edit distance functions: EDRDistMult_fast
,
EDRDistSakoeChibaMult_fast
,
EDRDistSakoeChiba_fast
,
ERPDistMult_fast
,
ERPDistSakoeChibaMult_fast
,
ERPDistSakoeChiba_fast
,
ERPDistSakoeChiba
,
ERPDist_fast
, ERPDist
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