View source: R/NNCTFunctions.r
cov.seg.coeff | R Documentation |
Returns the covariance matrix of the segregation coefficients in a multi-class case based on
the NNCT, ct
. The covariance matrix is of dimension k(k+1)/2 \times k(k+1)/2 and its entry i,j correspond to the
entries in the rows i and j of the output of ind.seg.coeff(k)
.
The segregation coefficients in the multi-class case are the extension of Pielou's segregation coefficient
for the two-class case.
These covariances are valid under RL or conditional on Q and R under CSR.
The argument covN
is the covariance matrix of N_{ij} (concatenated rowwise).
See also (\insertCiteceyhan:SiM-seg-ind2014;textualnnspat).
cov.seg.coeff(ct, covN)
ct |
A nearest neighbor contingency table |
covN |
The k^2 \times k^2 covariance matrix of row-wise vectorized entries of NNCT |
The k(k+1)/2 x k(k+1)/2 covariance matrix of the segregation coefficients for the multi-class case
based on the NNCT, ct
Elvan Ceyhan
seg.coeff
, var.seg.coeff
, cov.nnct
and cov.nnsym
n<-20 #or try sample(1:20,1) Y<-matrix(runif(3*n),ncol=3) ipd<-ipd.mat(Y) cls<-sample(1:2,n,replace = TRUE) #or try cls<-rep(1:2,c(10,10)) ct<-nnct(ipd,cls) W<-Wmat(ipd) Qv<-Qvec(W)$q Rv<-Rval(W) varN<-var.nnct(ct,Qv,Rv) covN<-cov.nnct(ct,varN,Qv,Rv) cov.seg.coeff(ct,covN) #cls as a factor na<-floor(n/2); nb<-n-na fcls<-rep(c("a","b"),c(na,nb)) ct<-nnct(ipd,fcls) cov.seg.coeff(ct,covN) ############# n<-40 Y<-matrix(runif(3*n),ncol=3) cls<-sample(1:4,n,replace = TRUE) #or try cls<-rep(1:2,c(10,10)) ipd<-ipd.mat(Y) ct<-nnct(ipd,cls) W<-Wmat(ipd) Qv<-Qvec(W)$q Rv<-Rval(W) varN<-var.nnct(ct,Qv,Rv) covN<-cov.nnct(ct,varN,Qv,Rv) cov.seg.coeff(ct,covN)
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