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neffIncomp <- function (x) {
# effective number of parties for incomplete data
# assumes residual category to be the last item!
P <- sum(x) # number of seats
R <- x[length(x)] # last item = residual category (assumed!)
A <- x[1:length(x)-1] # exclude last item ( = exclude residual)
PL <- agrmt::minnz(A) # smallest non-zero component reported
# requires minnz() from agrmt package (non-zero minimum)
noN <- P^2/(R + sum(A^2)) # f(R) = R, residual not squared ("simple")
lowN <- P^2/(R^2 + sum(A^2)) # f(R) = R^2 ( = residual included)
highN <- P^2/(sum(A^2)) # f(R) = 0, residual excluded
leastN <- P^2/(R*PL + sum(A^2)) # f(R) = least component
M <- ifelse (min(R^2, R*PL) == R*PL, leastN, lowN) # lower of R ^2 and PL
B <- mean(c(highN,M)) # best estimate
r <- list(Neff = B, simple = noN, low = lowN, least = leastN, high = highN)
return(r)
}
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