harbinger (version 1.2.747)

harutils: Harbinger Utilities

Description

Utility object that groups common distance measures, threshold heuristics, and outlier grouping rules used by Harbinger detectors.

Usage

harutils()

Value

A harutils object exposing the helper functions.

Details

Provided helpers include:

• L1 and L2 distance aggregations over vectors or rows of matrices/data frames.

• Thresholding heuristics: boxplot-based (IQR), Gaussian 3-sigma, and a ratio-based rule.

• Grouping strategies for contiguous outliers: keep first index or keep highest-magnitude index.

• Optional fuzzification over detections to propagate influence within a tolerance window.

These utilities centralize common tasks and ensure consistent behavior across detectors.

References

• Tukey JW (1977). Exploratory Data Analysis. Addison-Wesley. (boxplot/IQR heuristic)

• Shewhart WA (1931). Economic Control of Quality of Manufactured Product. D. Van Nostrand. (three-sigma rule)

• Silva, E. P., Balbi, H., Pacitti, E., Porto, F., Santos, J., Ogasawara, E. Cutoff Frequency Adjustment for FFT-Based Anomaly Detectors. In: Simpósio Brasileiro de Banco de Dados (SBBD). SBC, 14 Oct. 2024. doi:10.5753/sbbd.2024.243319

Examples

# Basic usage of utilities
utils <- harutils()

# Compute L2 distance on residuals
res <- c(0.1, -0.5, 1.2, -0.3)
d2 <- utils$har_distance_l2(res)
print(d2)

# Apply 3-sigma outlier rule and keep only first index of contiguous runs
idx <- utils$har_outliers_gaussian(d2)
flags <- utils$har_outliers_checks_firstgroup(idx, d2)
print(which(flags))