Flag local outliers using dbscan::lof()
flag_local_outliers(
df,
context,
vars = context,
min_points = 30,
geo_rel_col = "rel_metres_adj",
geo_rel_thresh = 100,
iqrMult = 2,
...
)
Dataframe with context
and all other columns defining the space
in which to look for outliers (usually environmental variables such as
climate or satellite variables)
Character. Name of columns defining context.
Character. Name of column(s) to investigate for outliers
Numeric. Don't attempt reverse jackknife calculations unless there are at least this number of data points.
Character. Name of column containing geographic
reliability information. Set to NULL
to ignore.
Numeric. Threshold in geo_rel_col
below which to
filter that row from analysis. Needed for, say, coarse spatial reliability
but satellite variables (e.g. no point checking if a point is an outlier
against satellite variables (with resolution of, say 30 m) if the geographic
reliability of that point is 10 km). Ignored if geo_rel_col
is NULL
.
Used in quantile(x, probs = 0.75) + iqrMult * IQR(x)
to set
the threshold for an outlier. e.g. ggplot2::geom_boxplot()
default value is
1.5
.
Passed to dbscan::lof()
. e.g. minPts
argument
tibble