funs.seg.coeff | R Documentation |
Two functions: Pseg.coeff
and seg.coeff
.
Each function computes segregation coefficients based on NNCTs.
The function Pseg.coeff
computes Pielou's segregation coefficient (\insertCitepielou:1961;textualnnspat)
for the two-class case (i.e., based on 2 \times 2 NNCTs)
and seg.coeff
is the extension of Pseg.coeff
to the multi-class case (i.e. for k \times k NNCTs with k ≥ 2)
and provides a k \times k matrix of segregation coefficients
(\insertCiteceyhan:SiM-seg-ind2014;textualnnspat).
Both functions use the same argument, ct
, for NNCT.
Pielou's segregation coefficient (for two classes) is S_P = 1-(N_{12} + N_{21})/(E[N_{12}] + E[N_{21}]) and the extended segregation coefficents (for k ≥ 2 classes) are S_c = 1 -(N_{ii})/(E[N_{ii}]) for the diagonal cells in the NNCT and S_c = 1 -(N_{ij} + N_{ji})/(E[N_{ij}] + E[N_{ji}]) for the off-diagonal cells in the NNCT.
Pseg.coeff(ct) seg.coeff(ct)
ct |
A nearest neighbor contingency table, used in both functions |
Pseg.coeff
returns Pielou's segregation coefficient for 2 \times 2 NNCT
seg.coeff
returns a k \times k matrix of segregation coefficients (which are extended versions
of Pielou's segregation coefficient)
Elvan Ceyhan
Elvan Ceyhan
seg.ind
, Zseg.coeff.ct
and Zseg.coeff
#Examples for Pseg.coeff 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) ct Pseg.coeff(ct) #cls as a factor na<-floor(n/2); nb<-n-na fcls<-rep(c("a","b"),c(na,nb)) ct<-nnct(ipd,fcls) Pseg.coeff(ct) ############# ct<-matrix(sample(1:25,9),ncol=3) #Pseg.coeff(ct) #Examples for seg.coeff 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) ct seg.coeff(ct) #cls as a factor na<-floor(n/2); nb<-n-na fcls<-rep(c("a","b"),c(na,nb)) ct<-nnct(ipd,fcls) seg.coeff(ct) ############# 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) seg.coeff(ct)
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