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 |

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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