## 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