Fhat(obj1, obj2, nx=sqrt(n), ny=sqrt(n), dist.fhat=all.dists,
plot.it=T)
"spp" representing a spatial point pattern, or a data frame
or matrix with first two columns containing locations of a point pattern.
"spp" representing a spatial point pattern,
or a data frame or matrix with first two columns containing the origins
from which the distances to the points in
obj1 are to be computed.
See DETAILS for computation of
Fhat.
obj2 is missing, a grid of size (
nx by
ny) is computed to be used as
set of origins.
Defaults to the square root of the total number of points in
obj1.
Fhat values are desired. See DETAILS. By default,
all distances between
obj1 and
obj2 will be used.
TRUE.
Fhat was computed.
The second column contains the corresponding
Fhat values.
plot.it=TRUE, a plot of
Fhat versus distance is produced.
Fhat provides an estimate of
F(y),
the proportion of points on a grid (
obj2) within distance
y
of the nearest point in the original pattern (
obj1).
For a completely spatially random process without edge effects, the theoretical
distribution of
F(y) is:
F(y) = 1 - exp(-pi * intensity * y^2)
where the intensity is the number of points per unit area.
If
obj2 is not supplied, an origin grid with dimension (
nx x
ny) is
created on the same area as the original data. The distances between each
origin in
obj2 and its nearest neighbor in
obj1 are computed using
find.neighbor
.
Diggle, Peter J. (1983). Statistical Analysis of Spatial Point Patterns. Academic Press, London.
lans.fhat <- Fhat(lansing)