sharedNNmc: The Shared NN Vectors for Multiple Classes

In nnspat: Nearest Neighbor Methods for Spatial Patterns

The Shared NN Vectors for Multiple Classes

Description

Returns a matrix with k rows where each row is the vector of number of points with shared NNs, Q_i=(Q_{i0},Q_{i1},…) where Q_{ij} is the number of class i points that are NN to class j points. The function also returns the indices of columns with nonzero sums as a vector.

The output matrix of shared NNs is used in testing symmetry in shared NN structure (i.e. Q-symmetry or Pielou's second type of symmetry), e.g., in functions Qsym.ct and Qsym.test.

See also (\insertCitepielou:1961,ceyhan:SWJ-spat-sym2014;textualnnspat) and the references therein.

Usage

sharedNNmc(x, lab, is.ipd = TRUE, ...)

Arguments

x	The IPD matrix (if is.ipd=TRUE) or a data set of points in matrix or data frame form where points correspond to the rows (if is.ipd = FALSEALSE).
lab	The vector of class labels (numerical or categorical)
is.ipd	A logical parameter (default=TRUE). If TRUE, x is taken as the inter-point distance matrix (IPD matrix), otherwise, x is taken as the data set with rows representing the data points.
...	are for further arguments, such as method and p, passed to the dist function.

Value

Qval returns the Q value Qvec returns a list with two elements

q	the Q value, the number of shared NNs
qvec	the vector of Q_j values

sharedNN returns a matrix with 2 rows, where first row is the j values and second row is the corresponding vector of Q_j values Rvalthe R value, the number of reflexive NNs

Returns a list with two elements

Nv	A k-row matrix of shared NNs by class where each row of the matrix is the vector of number of points with shared NNs Q_i=(Q_{i0},Q_{i1},…) where Q_{ij} is the number of class i points that are NN to j points.
col.ind	The vector of indices of columns with nonzero sums

Author(s)

Elvan Ceyhan

References

\insertAllCited

See Also

Qval, Qvec and sharedNN

Examples

n<-20  #or try sample(1:20,1)
Y<-matrix(runif(3*n),ncol=3)
cls<-sample(1:2,n,replace = TRUE)  #or try cls<-rep(1:2,c(10,10))
ipd<-ipd.mat(Y)

sharedNNmc(ipd,cls)
sharedNNmc(Y,cls,is.ipd = FALSE)
sharedNNmc(Y,cls,is.ipd = FALSE,method="max")

#cls as a factor
na<-floor(n/2); nb<-n-na
fcls<-rep(c("a","b"),c(na,nb))
sharedNNmc(ipd,fcls)

#############
n<-40
Y<-matrix(runif(3*n),ncol=3)
cls<-sample(1:4,n,replace = TRUE)  #or try cls<-rep(1:2,c(10,10))
ipd<-ipd.mat(Y)

sharedNNmc(ipd,cls) 

nnspat documentation built on Aug. 30, 2022, 9:06 a.m.