BCI: The Bertin Classification Index

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/fastRcrit.R

Description

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

Usage

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BCI(x)

Arguments

x

A data matrix, table or array.

Details

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

Value

The criterion value.

Author(s)

Alexander Pilhoefer

See Also

kendalls

Examples

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#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)

extracat documentation built on July 17, 2018, 5:05 p.m.

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