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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.