Functions to impute large gaps within time series based on Dynamic Time Warping methods. It contains all required functions to create large missing consecutive values within time series and to fill them, according to the paper Phan et al. (2017), <doi:10.1016/j.patrec.2017.08.019>. Performance criteria are added to compare similarity between two signals (query and reference).
| Version: | 1.1 |
| Depends: | R (≥ 3.0.0) |
| Imports: | dtw, rlist, stats, e1071, entropy, lsa |
| Published: | 2018-07-11 |
| Author: | Camille Dezecache, T. T. Hong Phan, Emilie Poisson-Caillault |
| Maintainer: | Emilie Poisson-Caillault <emilie.poisson at univ-littoral.fr> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://mawenzi.univ-littoral.fr/DTWBI/ |
| NeedsCompilation: | no |
| Citation: | DTWBI citation info |
| In views: | MissingData |
| CRAN checks: | DTWBI results |
| Reference manual: | DTWBI.pdf |
| Package source: | DTWBI_1.1.tar.gz |
| Windows binaries: | r-devel: DTWBI_1.1.zip, r-release: DTWBI_1.1.zip, r-oldrel: DTWBI_1.1.zip |
| macOS binaries: | r-release (arm64): DTWBI_1.1.tgz, r-oldrel (arm64): DTWBI_1.1.tgz, r-release (x86_64): DTWBI_1.1.tgz, r-oldrel (x86_64): DTWBI_1.1.tgz |
| Old sources: | DTWBI archive |
| Reverse imports: | DTWUMI |
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