IncDTW (1.1.2)
Incremental Calculation of Dynamic Time Warping.
http://cran.rproject.org/web/packages/IncDTW
The Dynamic Time Warping (DTW) distance measure for time series allows nonlinear alignments of time series to match similar patterns in time series of different lengths and or different speeds. IncDTW is characterized by (1) the incremental calculation of DTW (reduces runtime complexity to a linear level for updating the DTW distance)  especially for life data streams or subsequence matching, (2) the vector based implementation of DTW which is faster because no matrices are allocated (reduces the space complexity from a quadratic to a linear level in the number of observations)  for all runtime intensive DTW computations, (3) the subsequence matching algorithm runDTW, that efficiently finds the kNN to a query pattern in a long time series, and (4) C++ in the heart. For details about DTW see the original paper "Dynamic programming algorithm optimization for spoken word recognition" by Sakoe and Chiba (1978) .
Maintainer:
Maximilian Leodolter
Author(s): Maximilian Leodolter
License: GPL (>= 2)
Uses: data.table, ggplot2, Rcpp, RcppParallel, scales, R.rsp, proxy, dtw, testthat, gridExtra, microbenchmark, knitr, rmarkdown, dtwclust, rucrdtw, parallelDist
Released about 1 month ago.
12 previous versions
 IncDTW_1.1.1. Released 3 months ago.
 IncDTW_1.1.0. Released 4 months ago.
 IncDTW_1.0.5. Released 8 months ago.
 IncDTW_1.0.4. Released 11 months ago.
 IncDTW_1.0.3. Released over 1 year ago.
 IncDTW_1.0.2. Released over 1 year ago.
 IncDTW_1.0.1. Released over 1 year ago.
 IncDTW_1.0.0. Released almost 2 years ago.
 IncDTW_0.1.3. Released almost 2 years ago.
 IncDTW_0.1.2. Released almost 2 years ago.
 IncDTW_0.1.1. Released about 2 years ago.
 IncDTW_0.1.0. Released about 2 years ago.
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Visit IncDTW on R Graphical Manual.