Imputation of Time Series Based on Dynamic Time Warping

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), . Performance criteria are added to compare similarity between two signals (query and reference).


Reference manual

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1.1 by Emilie Poisson-Caillault, 3 years ago

Browse source code at

Authors: Camille Dezecache , T. T. Hong Phan , Emilie Poisson-Caillault

Documentation:   PDF Manual  

Task views: Missing Data

GPL (>= 2) license

Imports dtw, rlist, stats, e1071, entropy, lsa

Imported by DTWUMI.

See at CRAN