tsdataleaks: Exploit Data Leakages in Time Series Forecasting Competitions

Forecasting competitions are of increasing importance as a mean to learn best practices and gain knowledge. Data leakage is one of the most common issues that can often be found in competitions. Data leaks can happen when the training data contains information about the test data. For example: randomly chosen blocks of time series are concatenated to form a new time series, scale-shifts, repeating patterns in time series, white noise is added in the original time series to form a new time series, etc. 'tsdataleaks' package can be used to detect data leakages in a collection of time series.

Version: 2.1.1
Depends: R (≥ 3.6.0)
Imports: stats, tibble (≥ 1.4.1), ggplot2 (≥ 3.0.0), dplyr (≥ 1.0.0), tidyr (≥ 1.1.0), slider, purrr, utils, cowplot, plyr, viridis
Suggests: testthat (≥ 2.1.0), knitr, rmarkdown
Published: 2024-02-06
Author: Thiyanga S. Talagala ORCID iD [aut, cre]
Maintainer: Thiyanga S. Talagala <ttalagala at sjp.ac.lk>
BugReports: https://github.com/thiyangt/tsdataleaks/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/thiyangt/tsdataleaks
NeedsCompilation: no
Materials: README
In views: TimeSeries
CRAN checks: tsdataleaks results

Documentation:

Reference manual: tsdataleaks.pdf
Vignettes: tsdataleaks

Downloads:

Package source: tsdataleaks_2.1.1.tar.gz
Windows binaries: r-prerel: tsdataleaks_2.1.1.zip, r-release: tsdataleaks_2.1.1.zip, r-oldrel: tsdataleaks_2.1.1.zip
macOS binaries: r-prerel (arm64): tsdataleaks_2.1.1.tgz, r-release (arm64): tsdataleaks_2.1.1.tgz, r-oldrel (arm64): tsdataleaks_2.1.1.tgz, r-prerel (x86_64): tsdataleaks_2.1.1.tgz, r-release (x86_64): tsdataleaks_2.1.1.tgz

Linking:

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