## S3 method for class 'ppx':
nnwhich(X, \dots, k=1)"ppx").coords.ppx to determine
which coordinates should be used.kth nearest neighbour.kth nearest neighbour). If k = 1 (the default), the return value is a
numeric vector v giving the indices of the nearest neighbours
(the nearest neighbout of the ith point is
the jth point where j = v[i]).
If k is a single integer, then the return value is a
numeric vector giving the indices of the
kth nearest neighbours.
If k is a vector, then the return value is a
matrix m such that m[i,j] is the
index of the k[j]th nearest neighbour for the
ith data point.
NA is returned if there is only one point
in the point pattern.k is specified, the algorithm finds
each point's kth nearest neighbour. The function nnwhich is generic. This is the method
for the class "ppx".
If there are no points in the pattern,
a numeric vector of length zero is returned.
If there is only one point,
then the nearest neighbour is undefined, and a value of NA
is returned. In general if the number of points is less than or equal
to k, then a vector of NA's is returned.
To evaluate the distance between a point and its nearest
neighbour, use nndist.
To find the nearest neighbours from one point pattern
to another point pattern, use nncross.
By default, both spatial and temporal coordinates are extracted.
To obtain the spatial distance between points in a space-time point
pattern, set temporal=FALSE.
nnwhich,
nndist,
nncrossdf <- data.frame(x=runif(5),y=runif(5),z=runif(5),w=runif(5))
X <- ppx(data=df)
m <- nnwhich(X)
m2 <- nnwhich(X, k=2)Run the code above in your browser using DataLab