tsoutliers
Detection of Outliers in Time Series
Detection of outliers in time series following the Chen and Liu (1993) <DOI:10.2307/2290724> procedure. Innovational outliers, additive outliers, level shifts, temporary changes and seasonal level shifts are considered.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.6-10 |
rolling linux/jammy R-4.5 | tsoutliers_0.6-10.tar.gz |
229.4 KiB |
0.6-10 |
rolling linux/noble R-4.5 | tsoutliers_0.6-10.tar.gz |
229.5 KiB |
0.6-10 |
rolling source/ R- | tsoutliers_0.6-10.tar.gz |
107.1 KiB |
0.6-10 |
latest linux/jammy R-4.5 | tsoutliers_0.6-10.tar.gz |
229.4 KiB |
0.6-10 |
latest linux/noble R-4.5 | tsoutliers_0.6-10.tar.gz |
229.5 KiB |
0.6-10 |
latest source/ R- | tsoutliers_0.6-10.tar.gz |
107.1 KiB |
0.6-10 |
2026-04-26 source/ R- | tsoutliers_0.6-10.tar.gz |
107.1 KiB |
0.6-10 |
2026-04-23 source/ R- | tsoutliers_0.6-10.tar.gz |
107.1 KiB |
0.6-10 |
2026-04-09 windows/windows R-4.5 | tsoutliers_0.6-10.zip |
232.8 KiB |
0.6-10 |
2025-04-20 source/ R- | tsoutliers_0.6-10.tar.gz |
107.1 KiB |