DTWBI
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), doi:10.1016/j.patrec.2017.08.019. Performance criteria are added to compare similarity between two signals (query and reference).
- Version1.1
- R version≥ 3.0.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release07/11/2018
Documentation
Team
Emilie Poisson-Caillault
Camille Dezecache
T. T. Hong Phan
Insights
Last 30 days
This package has been downloaded 203 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,491 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 28, 2024 with 25 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports5 packages
- Reverse Imports1 package