View source: R/NNCTFunctions.R
| NNsub | R Documentation |
Returns the index (indices) of the nearest neighbor(s) of subject i
(other than subject i) among the indices of points
provided in the subsample ss using
the given data set or IPD matrix x.
The indices in ss determine the
columns of the IPD matrix to be used in this function.
It will yield a vector if there are ties,
and subject indices correspond to rows
(i.e., rows 1:n ) if x
is the data set and to rows or columns
if x is the IPD matrix.
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.
NNsub(ss, x, i, is.ipd = TRUE, ...)
ss |
indices of subjects (i.e., row indices in the data set) among with the NN of subject is to be found |
x |
The IPD matrix (if |
i |
index of (i.e., row number for) the subject whose NN is to be found. |
is.ipd |
A logical parameter (default= |
... |
are for further arguments,
such as |
Returns a list with the elements
base.ind |
index of the base subject |
ss.ind |
the index (indices) i.e.,
row number(s) of the NN of subject |
ss.dis |
distance from subject |
Elvan Ceyhan
NN and kNN
#3D data points
n<-20 #or try sample(1:20,1)
Y<-matrix(runif(3*n),ncol=3)
ipd<-ipd.mat(Y)
#indices of the subsample ss
ss<-sample(1:n,floor(n/2),replace=FALSE)
NNsub(ss,ipd,2)
NNsub(ss,Y,2,is.ipd = FALSE)
NNsub(ss,ipd,5)
#1D data points
n<-15
X<-as.matrix(runif(n))# need to be entered as a matrix with one column
#(i.e., a column vector), hence X<-runif(n) would not work
ipd<-ipd.mat(X)
#two class case
clab<-sample(1:2,n,replace=TRUE) #class labels
#indices of the subsample ss
ss<-sample(1:n,floor(n/2),replace=FALSE)
NNsub(ss,ipd,2)
NNsub(ss,ipd,5)
#with possible ties in the data
Y<-matrix(round(runif(60)*10),ncol=3)
ipd<-ipd.mat(Y)
ss<-sample(1:20,10,replace=FALSE) #class labels
NNsub(ss,ipd,2)
NNsub(ss,ipd,5)
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