| NNdist | R Documentation |
Returns the distances between subjects and their NNs. The output is an n \times 2 matrix where n is the data size and first column is the subject index and second column contains the corresponding distances to NN subjects.
The argument is.ipd is a logical argument
(default=TRUE) to determine the structure of the argument x.
If TRUE, x is taken to be
the inter-point distance (IPD) matrix,
and if FALSE, x is taken to be the data set
with rows representing the data points.
NNdist(x, is.ipd = TRUE, ...)
x |
The IPD matrix (if |
is.ipd |
A logical parameter (default= |
... |
are for further arguments,
such as |
Returns an n \times 2 matrix where n is data size (i.e., number of subjects) and first column is the subject index and second column is the NN distances.
Elvan Ceyhan
kthNNdist, kNNdist,
and NNdist2cl
#3D data points n<-20 #or try sample(1:20,1) Y<-matrix(runif(3*n),ncol=3) ipd<-ipd.mat(Y) NNdist(ipd) NNdist(Y,is.ipd = FALSE) NNdist(Y,is.ipd = FALSE,method="max") #1D data points X<-as.matrix(runif(5)) # need to be entered as a matrix with one column #(i.e., a column vector), hence X<-runif(5) would not work ipd<-ipd.mat(X) NNdist(ipd) NNdist(X,is.ipd = FALSE)