Description Usage Arguments Details Value Author(s) See Also Examples
Computes the Bertin Classification Index for a contingency table of any dimensions.
1 | BCI(x)
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x |
A data matrix, table or array. |
The BCI is the Bertin Classification Criterion (BCC) normalized by the BCC value under independence.
The criterion value.
Alexander Pilhoefer
kendalls
1 2 3 4 5 6 7 8 9 10 11 12 13 | #for an unoptimized matrix we take the minimum of BCI(M) and BCI(M[,12:1])
M <-arsim(1000, c(12,12), 3)
min(BCI(M), BCI(M[,12:1]))
#an strongly related alternative (for two-way data)
kendalls(M)
M2 <- optile(M, iter = 100)
BCI(M2)
kendalls(M2)
M3 <-arsim(100000, c(12,13,15), 4,noise=0.2,shuffle=FALSE)
BCI(M3)
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