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DTWUMI

1.0

Imputation of Multivariate Time Series Based on Dynamic Time Warping

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2.5Kdownloads / year
test coverage
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Overview

About
Maintained by POISSON-CAILLAULT EmilieFirst published 2018-07-131 releasesCRAN page ↗

Functions to impute large gaps within multivariate time series based on Dynamic Time Warping methods. Gaps of size 1 or inferior to a defined threshold are filled using simple average and weighted moving average respectively. Larger gaps are filled using the methodology provided by Phan et al. (2017) DOI:10.1109/MLSP.2017.8168165: a query is built immediately before/after a gap and a moving window is used to find the most similar sequence to this query using Dynamic Time Warping. To lower the calculation time, similar sequences are pre-selected using global features. Contrary to the univariate method (package 'DTWBI'), these global features are not estimated over the sequence containing the gap(s), but a feature matrix is built to summarize general features of the whole multivariate signal. Once the most similar sequence to the query has been identified, the adjacent sequence to this window is used to fill the gap considered. This function can deal with multiple gaps over all the sequences componing the input multivariate signal. However, for better consistency, large gaps at the same location over all sequences should be avoided.

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Slowest check: 1.2 min · r-oldrel-windows-x86_64
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  • NOTE2026-03-10
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Documentation

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References docs
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Dependencies

Declared dependencies
6 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.0.0
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Listed in earlier versions (3)
no longer listed · 1.0
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Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2018-07-13
Total releases
1 / 8 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 3.0.0
Bundled data
18 KB / 1 file
Download size
34 KB
Installed size
not tracked yet
With dependencies
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citation("DTWUMI")

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APA

Balamuta, J. J. (2026). R Observatory: Metrics for DTWUMI version 1.0 [Data set]. HJJB, LLC. Data release v2026-08-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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