lookout
Leave One Out Kernel Density Estimates for Outlier Detection
Outlier detection using leave-one-out kernel density estimates and extreme value theory. The bandwidth for kernel density estimates is computed using persistent homology, a technique in topological data analysis. Using peak-over-threshold method, a generalized Pareto distribution is fitted to the log of leave-one-out kde values to identify outliers.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.0.1 |
rolling linux/jammy R-4.5 | lookout_2.0.1.tar.gz |
129.8 KiB |
2.0.1 |
rolling linux/noble R-4.5 | lookout_2.0.1.tar.gz |
129.8 KiB |
2.0.1 |
rolling source/ R- | lookout_2.0.1.tar.gz |
96.0 KiB |
2.0.1 |
latest linux/jammy R-4.5 | lookout_2.0.1.tar.gz |
129.8 KiB |
2.0.1 |
latest linux/noble R-4.5 | lookout_2.0.1.tar.gz |
129.8 KiB |
2.0.1 |
latest source/ R- | lookout_2.0.1.tar.gz |
96.0 KiB |
2.0.1 |
2026-04-26 source/ R- | lookout_2.0.1.tar.gz |
96.0 KiB |
2.0.1 |
2026-04-23 source/ R- | lookout_2.0.1.tar.gz |
96.0 KiB |
2.0.1 |
2026-04-09 windows/windows R-4.5 | lookout_2.0.1.zip |
133.2 KiB |
0.1.4 |
2025-04-20 source/ R- | lookout_0.1.4.tar.gz |
100.8 KiB |