UncertCoef: Uncertainty Coefficient

In DescTools: Tools for Descriptive Statistics

Uncertainty Coefficient

Description

The uncertainty coefficient U(C|R) measures the proportion of uncertainty (entropy) in the column variable Y that is explained by the row variable X. The function has interfaces for a table, a matrix, a data.frame and for single vectors.

Usage

UncertCoef(x, y = NULL, direction = c("symmetric", "row", "column"), 
           conf.level = NA, p.zero.correction = 1/sum(x)^2, ...)

Arguments

x	a numeric vector, a factor, matrix or data frame.
y	NULL (default) or a vector, an ordered factor, matrix or data frame with compatible dimensions to x.
direction	direction of the calculation. Can be "row" (default) or "column", where "row" calculates UncertCoef (R|C) ("column dependent").
conf.level	confidence level of the interval. If set to NA (which is the default) no confidence interval will be calculated.
p.zero.correction	slightly nudge zero values so that their logarithm can be calculated
...	further arguments are passed to the function table, allowing i.e. to set useNA. This refers only to the vector interface.

Details

The uncertainty coefficient is computed as

U(C|R) = \frac{H(X) + H(Y) - H(XY)}{H(Y)}

and ranges from [0, 1].

Value

Either a single numeric value, if no confidence interval is required,
or a vector with 3 elements for estimate, lower and upper confidence intervall.

Author(s)

Andri Signorell <[e-mail]> strongly based on code from Antti Arppe <[e-mail]>

References

Theil, H. (1972), Statistical Decomposition Analysis, Amsterdam: North-Holland Publishing Company.

See Also

Entropy, Lambda, Assocs

Examples

# example from Goodman Kruskal (1954)

m <- as.table(cbind(c(1768,946,115), c(807,1387,438), c(189,746,288), c(47,53,16)))
dimnames(m) <- list(paste("A", 1:3), paste("B", 1:4))
m

# direction default is "symmetric"
UncertCoef(m)
UncertCoef(m, conf.level=0.95)

UncertCoef(m, direction="row")
UncertCoef(m, direction="column")

DescTools documentation built on Sept. 26, 2024, 1:07 a.m.