Robust bandwidth estimation for kernel density estimation

Bandwidth matrices are estimated using either a robust version of the normal reference rule, or using the approach of Hyndman, Kandanaarachchi & Turner (2026).

Usage

kde_bandwidth(data, method = c("robust", "normal", "plugin", "lookout"), ...)

Arguments

data: A numeric matrix or data frame.
method: A character string giving the method to use. Possibilities are: "normal" (normal reference rule), "robust" (a robust version of the normal reference rule, the default), "plugin" (a plugin estimator), and "lookout" (the bandwidth matrix estimate of Hyndman, Kandanaarachchi & Turner, 2026).
...: Additional arguments are ignored unless method = "lookout", when they are passed to lookout::find_tda_bw().

Value

A matrix of bandwidths (or a scalar in the case of univariate data).

References

Rob J Hyndman, Sevvandi Kandanaarachchi & Katharine Turner (2026) "When lookout sees crackle: Anomaly detection via kernel density estimation", unpublished. https://robjhyndman.com/publications/lookout2/

Rob J Hyndman (2026) "That's weird: Anomaly detection using R", https://OTexts.com/weird/

Author

Rob J Hyndman

Examples

# Univariate bandwidth calculation
kde_bandwidth(oldfaithful$duration)
#> [1] 5.087698
# Bivariate bandwidth calculation
kde_bandwidth(oldfaithful[, c("duration", "waiting")])
#>           [,1]       [,2]
#> [1,]  40.53793   349.3449
#> [2,] 349.34486 22918.0734