Spatial
Distances and projection, centrography, nearest neighbours and K functions, hot spots, space-time tests and journey to crime.
| Function | What it computes | Command line and bindings |
|---|---|---|
hvdist() |
Great-circle distance | |
eqproj() |
Equal-area projection of longitude and latitude, and its inverse | |
cgstat() |
Mean centre and dispersion of points | |
cgmedn() |
Median centre of points | |
webpt() |
Centre of minimum distance | |
sdell() |
Standard deviational ellipse | |
cvhull() |
Convex hull of points | |
nnidx() |
Nearest-neighbour index | |
ripk() |
Ripley’s K function | |
ripenv() |
Envelopes of Ripley’s L function and a test of complete spatial randomness | |
fzmode() |
Fuzzy mode | |
kmpart() |
K-means partition of points | |
nnhclu() |
Nearest-neighbour hierarchical clustering | |
stacel() |
Search-circle hot-spot areas | |
rnnhcl() |
Risk-adjusted nearest-neighbour hierarchical clustering | |
hdbang() |
Head-bang smoothing | |
crwalk() |
Correlated random walk of a series of events | |
mantst() |
Mantel’s space-time test | |
stmavg() |
Spatial-temporal moving average | |
jtdecay() |
Distance-decay functions for journey to crime | |
jtsurf() |
Journey-to-crime surface | |
jtcal() |
Empirical distance decay from solved trips | |
jtacc() |
Accuracy of a journey-to-crime surface on a solved series | |
bjtc() |
Bayesian journey to crime | |
spwt() |
Spatial weights | |
gearc() |
Geary’s C | |
gorg() |
The general G of Getis and Ord | |
lmorn() |
Local Moran (LISA) | |
locgi() |
Local G and G* of Getis and Ord | |
dirmn() |
Directional mean and circular variance |
Each name links to its R help page, which gives the method, its source and a worked example. The other languages use the same names and the same arguments.