pdcDistTSListMult: Multi-variate Permutation Distribution Distance for a List of...
In Jakob-Bach/FastTSDistances: Fast dissimilarity computations for time series

Description Usage Arguments Value References See Also

Multi-variate version of pdcDistTSList.

1	pdcDistTSListMult(tsList, subSequenceLength = NULL)

tsList

1) A list of numeric matrixes (multi-variate time series). The dissimilarity of the list to itself (each time series to each time series) will be computed, resulting in a symmetric dissimilarity matrix. 2) A list with two components, each being a list of numeric matrixes (multi-variate time series). The dissimilarity of each time series from the 1st component to each time series from the 2nd component will be computed. The entropy heuristic is only computed with the second component (for comparability to previously computed distances). 1+2) Each time series should each have a minimum element (row) count of two and all the same number of attributes (columns)).

subSequenceLength

Number of elements which form each subsequence. Will be determined as integer in [2,7] by a heuristic if not provided.

The distance matrix with each entry being a numeric from the range [0,4*attributeCount].

Brandmaier, A. M. (2011). Permutation distribution clustering and structural equation model trees (Doctoral dissertation, Universität des Saarlandes, Saarbrücken).

Brandmaier, A. M. (2015). pdc: An R Package for Complexity-Based Clustering of Time Series. Journal of Statistical Software, 67(5), 1-23.

Other PDC functions: pdcDistTSList, pdcDistTwoTSMult, pdcDistTwoTS, pdcEntropyHeuristicMult, pdcEntropyHeuristic, pdcEntropy