This function allows specification of parameters that affect the output from
hotspot_classify.
hotspot_classify_params(
hotspot_prop = 0.1,
persistent_prop = 0.8,
recent_prop = 0.2,
critical_p = 0.05,
nb_dist = NULL,
include_self = TRUE,
p_adjust_method = NULL
)A list that can be used as the input to the params argument to
hotspot_classify.
A single numeric value specifying the minimum proportion of periods for which a cell must contain significant clusters of points before the cell can be classified as a hot or cold spot of any type.
A single numeric value specifying the minimum proportion of periods for which a cell must contain significant clusters of points before the cell can be classified as a persistent hot or cold spot.
A single numeric value specifying the proportion of periods that should be treated as being recent in the classification of emerging and former hotspots.
A threshold p-value below which values should be treated as being statistically significant.
The distance around a cell that contains the neighbours of
that cell, which are used in calculating the statistic. If this argument is
NULL (the default), nb_dist is set as cell_size *
sqrt(2) so that only the cells immediately adjacent to each cell are
treated as being its neighbours.
Should points in a given cell be counted as well as
counts in neighbouring cells when calculating the values of
Gi*
(if include_self = TRUE, the default) or
Gi*
(if include_self = FALSE) values? You are unlikely to want to change
the default value.
The method to be used to adjust p-values for
multiple comparisons. NULL (the default) uses the default method
used by p.adjust, but any of the character values in
stats::p.adjust.methods may be specified.