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hotspot_dbscan() to identify clusters
using the DBSCAN algorithm, as implemented in the dbscan package. Its
min_pts and eps parameters are selected
automatically by default from the number of points and nearest-neighbour
distances, respectively. Also added corresponding
autoplot() and autolayer() methods.hotspot_isoband() to generalise values in
regular square hotspot grids into tidy SF isobands with appropriate
visual representation (#81).hotspot_map() to produce quick maps of the
objects produced by functions in the hotspot_*() family, as
well as of generic sf objects. By default, maps produced by
hotspot_map() include a base map while those produced using
autoplot() methods do not.hotspot_layer() provides a
student-friendly wrapper around ggplot2::autolayer() for
adding sfhotspot results to custom ggplot2 maps.hotspot_gistar() and hotspot_classify()
now use the default Holm method when
p_adjust_method = NULL. P-values are adjusted once using
spdep::p.adjustSP(); hotspot_classify() no
longer applies a second adjustment across time periods. Use
p_adjust_method = "none" to retain unadjusted p-values
(#94).autoplot() and autolayer() methods
for hotspot_gistar() and hotspot_dual_kde()
results, and completed the plotting support for
hotspot_classify() results. Plot scales and legends now
reflect the semantics of each result, including the comparison method
used for dual KDE and significance/sign filtering for Gi* results. A new
website plotting article demonstrates each distinct behaviour
(#85).hotspot_clip() can now clip any type of geometry, not
just point data (#65, #78) and produces warnings if clipping changes the
geometry type of any features in a way that might create downstream
problems.hotspot_clip() now preserves the specialised
hspt_* class of results produced by other package functions
(#71).hotspot_gistar() results now have the specialised class
hspt_g, allowing downstream functions to identify
gistar as their primary value column (#82).hotspot_clip() no longer reports that zero rows were
removed when all input features fall within the clipping boundary
(#66).hotspot_clip() no longer suppresses warnings produced
by sf::st_intersection() other than the constant “attribute
variables are assumed to be spatially constant throughout all
geometries” (since this is rarely relevant).hotspot_gistar() now calculates KDE values for
longitude/latitude data by automatically transforming them to a
projected co-ordinate reference system and transforming the results back
afterwards (#68).hotspot_dual_kde() now calculates valid KDE values for
longitude/latitude data while using a common automatically selected
bandwidth for both layers, and checks that both point layers overlap the
analysis grid (#67).hotspot_gistar() now uses weighted counts to calculate
Gi* statistics and p-values when weights are supplied, and
autoplot()/autolayer() plot use weighted
counts when they are present (#86).st_transform_auto()
in KDE-related functions now correctly restores the original geographic
CRS rather than converting to EPSG:4326 even when another geographic CRS
was originally used (#89).st_transform_auto()
in hotspot_kde() and hotspot_gistar() now
ensures the same CRS is selected for both data and
grid (#90).hotspot_clip() added to extract points
from an SF object inside the boundary of a polygon (#57).st_transform_auto()
(#48).hotspot_grid() handles certain invalid polygon
geometries (#54).hotspot_grid() handles non-multipolygon input
geometries (#46).hotspot_dual_kde(), hotspot_gistar() and
hotspot_kde() now warn if KDE bandwidth is smaller than
cell size (#29).count_points_in_polygons() (which is used internally to
count points in all the hotspot_*() family of functions)
now respects quiet = TRUE (#52).count_points_in_polygons() now passes through columns
in the original dataset, which makes hotspot_count() more
useful (#41).hotspot_grid() if provided with polygons now bases the
grid on the boundary of the polygons rather than the convex hull of the
boundary (#42).memphis_precincts showing Memphis Police
Department precincts, which is required to test the new functionality of
hotspot_grid().hotspot_gistar() now extracts nearest neighbour
distance from provided grid and does not wrongly rely on (and report) an
automatically generated cell size (#38).geometry (#30).hotspot_kde() progress bar is now suppressed by
quiet = TRUE (#25).bandwidth_adjust (#32).covr dependency.hotspot_change() and corresponding methods
for autoplot() and autolayer() for measuring
change in the frequency of events between two time periods (#14).hotspot_dual_kde() for estimating
different relations between the density of two point layers (#1).memphis_population showing the 2020
population of the centroids of census blocks in Memphis, TN.weights argument to
hotspot_count(), hotspot_kde() and
hotspot_gistar().grid
argument to the hotspot_*() family of functions.hotspot_grid() added so users can create a
rectangular or hexagonal grid separately from counting points,
calculating KDE values, etc. This may be useful to use the same grid for
different datasets covering a similar area.... arguments were not passed on to
SpatialKDE::kde() as specified in the documentation.autoplot() methods for plotting the results
produced by hotspot_count(), hotspot_kde() and
hotspot_classify().bandwidth_adjust argument to
hotspot_kde() and hotspot_gistar() so that
bandwidth can be set relative to the default.hotspot_*()
family of functions was not clipped to the convex hull of the data, as
specified in the documentation.hotspot_classify() and
hotspot_classify_params() functions.\dontrun{} in some of the documentation
examples to \donttest{}.hotspot_count(), hotspot_kde() and
hotspot_gistar().These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.