ddhellingerpar {dad}R Documentation

Distance between discrete probability distributions given the probabilities on their common support

Description

Hellinger (or Matusita) distance between two discrete probability distributions on the same support (which can be a Cartesian product of qq sets) , given the probabilities of the states (which are qq-tuples) of the support.

Usage

ddhellingerpar(p1, p2)

Arguments

p1

array (or table) the dimension of which is qq. The first probability distribution on the support.

p2

array (or table) the dimension of which is qq. The second probability distribution on the support.

Details

The Hellinger distance between two discrete distributions p1p_1 and p2p_2 is given by: x(p1(x)p2(x))2\sqrt{ \sum_x{(\sqrt{p_1(x)} - \sqrt{p_2(x)})^2}}

Notice that some authors divide this expression by 2\sqrt{2}.

Author(s)

Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Sabine Demotes-Mainard

References

Deza, M.M. and Deza E. (2013). Encyclopedia of distances. Springer.

See Also

ddhellinger: Hellinger distance between two estimated discrete distributions, given samples.

Other distances: ddchisqsympar, ddjeffreyspar, ddjensenpar, ddlppar.

Examples

# Example 1
p1 <- array(c(1/2, 1/2), dimnames = list(c("a", "b"))) 
p2 <- array(c(1/4, 3/4), dimnames = list(c("a", "b"))) 
ddhellingerpar(p1, p2)

# Example 2
x1 <- data.frame(x = factor(c("A", "A", "A", "B", "B", "B")),
                 y = factor(c("a", "a", "a", "b", "b", "b")))                 
x2 <- data.frame(x = factor(c("A", "A", "A", "B", "B")),
                 y = factor(c("a", "a", "b", "a", "b")))
p1 <- table(x1)/nrow(x1)                 
p2 <- table(x2)/nrow(x2)
ddhellingerpar(p1, p2)

[Package dad version 4.1.2 Index]