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Changelog

Source: NEWS.md

lookout (development version)

  • The exact density estimates (fast = FALSE) now use a fixed-radius neighbour search via dbscan::frNN(), so memory no longer grows with NROW(X)^2. Results are unchanged up to rounding.
  • Nearest neighbour searches now use dbscan rather than RANN, which is no longer imported.
  • The default is now fast = NROW(X) > 10000.
  • lookout() gives a more helpful error when the GPD cannot be fitted because too many observations have no neighbours within the bandwidth.
  • mvscale() now matches weird::mvscale(), with a robust MCD covariance estimate by default. This changes the scaled data used by lookout() and persisting_outliers() when scale = TRUE.
  • Fixed the Epanechnikov kernel scaling for multivariate data.
  • The fast argument of find_tda_bw() is deprecated and ignored.
  • Now requires R >= 4.1.0.
  • Bug fixes and documentation improvements.

lookout 2.0.2

CRAN release: 2026-07-21

  • Compatibility with mlpack 4.8.0, which changed the value returned by mlpack::emst().

lookout 2.0.1

CRAN release: 2026-03-26

  • find_tda_bw() now much faster, especially for large data sets, by using MST instead of Rips complex to compute persistent homology.

lookout 2.0.0

CRAN release: 2026-01-19

  • Updated lookout algorithm as per Hyndman, Kandanaarachchi and Turner (2026).
  • Added mvscale() to do robust multivariate scaling.
  • Exported find_tda_bw().

lookout 0.1.4

CRAN release: 2022-10-13

  • First CRAN version, based on Kandanaarachchi and Hyndman (JCGS, 2022).