envoutliers
Methods for Identification of Outliers in Environmental Data
Three semi-parametric methods for detection of outliers in environmental data based on kernel regression and subsequent analysis of smoothing residuals. The first method (Campulova, Michalek, Mikuska and Bokal (2018) <DOI: 10.1002/cem.2997>) analyzes the residuals using changepoint analysis, the second method is based on control charts (Campulova, Veselik and Michalek (2017) <DOI: 10.1016/j.apr.2017.01.004>) and the third method (Holesovsky, Campulova and Michalek (2018) <DOI: 10.1016/j.apr.2017.06.005>) analyzes the residuals using extreme value theory (Holesovsky, Campulova and Michalek (2018) <DOI: 10.1016/j.apr.2017.06.005>).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.0 |
rolling source/ R- | envoutliers_1.1.0.tar.gz |
43.9 KiB |
1.1.0 |
latest source/ R- | envoutliers_1.1.0.tar.gz |
43.9 KiB |
1.1.0 |
2026-04-23 source/ R- | envoutliers_1.1.0.tar.gz |
43.9 KiB |
1.1.0 |
2026-04-09 windows/windows R-4.5 | envoutliers_1.1.0.zip |
212.6 KiB |