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To cite the associated publication use:
Phan T, Poisson-Caillault E, Bigand A, Lefebvre A (2017). “DTW-Approach for uncorrelated multivariate time series imputation.” In 27th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2017, Tokyo, Japan, September 25-28, 2017, 1–6. doi:10.1109/MLSP.2017.8168165, https://doi.org/10.1109/MLSP.2017.8168165.
This package relies on DTW algorithm:
Giorgino T (2009). “Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package.” Journal of Statistical Software, 31(7), 1–24. http://www.jstatsoft.org/v31/i07/.
Corresponding BibTeX entries:
@InProceedings{, title = {DTW-Approach for uncorrelated multivariate time series imputation}, booktitle = {27th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2017, Tokyo, Japan, September 25-28, 2017}, author = {Thi-Thu-Hong Phan and Emilie Poisson-Caillault and Andre Bigand and Alain Lefebvre}, journal = {Pattern Recognition Letters}, year = {2017}, pages = {1--6}, crossref = {DBLP:conf/mlsp/2017}, url = {https://doi.org/10.1109/MLSP.2017.8168165}, doi = {10.1109/MLSP.2017.8168165}, timestamp = {Wed, 16 May 2018 14:25:05 +0200}, biburl = {https://dblp.org/rec/bib/conf/mlsp/PhanCBL17}, bibsource = {dblp computer science bibliography, https://dblp.org}, }
@Article{, title = {Computing and Visualizing Dynamic Time Warping Alignments in {R}: The {dtw} Package}, author = {Toni Giorgino}, journal = {Journal of Statistical Software}, year = {2009}, volume = {31}, number = {7}, pages = {1--24}, url = {http://www.jstatsoft.org/v31/i07/}, }
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.