EDRDistSakoeChiba_fast: (Fast) Edit Distance on Real Sequence and Sakoe-Chiba Window

In Jakob-Bach/FastTSDistances: Fast dissimilarity computations for time series

Description

Computes the Edit distance on Real Sequence as described by Chen, Özsu and Oria (2005), constraining the possible matches to a maximum index difference of windowSize as desribed by Sakoe and Chiba (1978). The coding is inspired by the TSdist::EDRDistance() method, but faster because point-to-point distances computation is integrated into the C++ code.

Usage

EDRDistSakoeChiba_fast(x, y, epsilon, windowSize)

Arguments

x	1st numeric vector/time series.
y	2nd numeric vector/time series.
epsilon	Maximum distance between two time series elements to count a match.
windowSize	The maximum index difference which is considered when matching elements

Details

Despite the name, it is not really a distance in the strict sense, as EDR violates the triangular inequality.

Value

The distance as double (not-a-number if matching is not possible as the time series lengths differ more than windowSize).

References

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.

Sakoe, H., & Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE transactions on acoustics, speech, and signal processing, 26(1), 43-49.

See Also

Other Edit distance functions: EDRDistMult_fast, EDRDistSakoeChibaMult_fast, EDRDist_fast, ERPDistMult_fast, ERPDistSakoeChibaMult_fast, ERPDistSakoeChiba_fast, ERPDistSakoeChiba, ERPDist_fast, ERPDist

Jakob-Bach/FastTSDistances documentation built on May 13, 2019, 1:15 p.m.