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extracat (version 1.7-6)

BCI: The Bertin Classification Index

Description

Computes the Bertin Classification Index for a contingency table of any dimensions.

Usage

BCI(x)

Arguments

x

A data matrix, table or array.

Value

The criterion value.

Details

The BCI is the Bertin Classification Criterion (BCC) normalized by the BCC value under independence.

See Also

kendalls

Examples

Run this code
# NOT RUN {
#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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