dad (version 4.1.6)

ddjensen: Divergence between probability distributions of discrete variables given samples

Description

Jensen-Shannon divergence between two multivariate (\(q > 1\)) or univariate (\(q = 1\)) discrete probability distributions, estimated from samples.

Usage

ddjensen(x1, x2)

Value

The distance between the two probability distributions.

Arguments

x1, x2

vectors or data frames of \(q\) columns (can also be tibbles).

If they are data frames and have not the same column names, there is a warning.

Author

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

Details

Let \(p_1\) and \(p_2\) denote the estimated probability distributions of the discrete samples \(x_1\) and \(x_2\). The Jensen-Shannon divergence between the discrete probability distributions of the samples are computed using the ddjensenpar function.

References

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

See Also

ddjensenpar: Jensen-Shannon distance between two discrete distributions, given the probabilities on their common support.

Other distances: ddchisqsym, ddhellinger, ddjeffreys, ddlp.

Examples

# Example 1
x1 <- c("A", "A", "B", "B")
x2 <- c("A", "A", "A", "B", "B")
ddjensen(x1, x2)

# 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")))
ddjensen(x1, x2)