Flag outliers via dBBMM-Z (isotropic submodel of dBGB)

Convenience wrapper around mt_flag_outliers_dbgb that fixes variance = "dbbmm". Mathematically the \(\sigma^2_{\parallel} = \sigma^2_{\perp}\) submodel of the dBGB primitive: the bivariate residual is normalised by a single isotropic motion variance and the per-axis decomposition is discarded. Faster (one 1-D Brent fit per window rather than two) and emits a simpler output schema (sigma2_motion instead of sigma2_motion_para / sigma2_motion_orth; bridge_z_para / bridge_z_orth not present). The flagging Z is the chisq scalar Rayleigh-Z and the parametric threshold helpers (Bonferroni / BH-FDR) apply directly.

Usage

mt_flag_outliers_dbbmm(x, ...)

Arguments

x

A move2 object. Single- or multi-track. Auto- projected to a per-track local AEQD if input is lon/lat.

...

Further arguments passed to mt_flag_outliers_dbgb. Do not pass variance; it is fixed at "dbbmm" here – call mt_flag_outliers_dbgb directly to vary it. The per-channel z_threshold_method options ("bonferroni", "bh_fdr", "gap") are forwarded; under variance = "dbbmm" only the chisq channel exists, so the envelope rule reduces to a scalar Z test.

Value

The input object with bridge-Z outlier-detection columns attached; see mt_flag_outliers_dbgb for the column schema. Per-axis columns (bridge_z_para, bridge_z_orth, sigma2_motion_para, sigma2_motion_orth) are not emitted under variance = "dbbmm".

See also

mt_flag_outliers_dbgb for the full state- aware bridge primitive with directional decomposition; mt_flag_outliers_bridge for the leverage-immune static bridge primitive.

Examples

if (FALSE) { # \dontrun{
library(move2)
x <- mt_read(system.file("extdata/Pettstadt1-14053.csv.gz",
                           package = "move2utils"))
x <- x[!sf::st_is_empty(x), ]
res <- mt_flag_outliers_dbbmm(x)
} # }