matddjeffreys {dad} | R Documentation |
Matrix of distances between discrete probability densities given samples
Description
Computes the matrix of Jeffreys divergences between several multivariate or univariate discrete probability distributions, estimated from samples.
Usage
matddjeffreys(x)
Arguments
x |
object of class |
Value
Positive symmetric matrix whose order is equal to the number of data frames (or distributions), consisting of the pairwise Jeffreys divergences between the distributions.
Author(s)
Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Sabine Demotes-Mainard
References
Deza, M.M. and Dezaz E. (2013). Encyclopedia of distances. Springer.
See Also
matddjeffreyspar
for discrete probability densities, given the probabilities on the same support.
Examples
# Example 1
x1 <- data.frame(x = factor(c("A", "A", "B", "B")))
x2 <- data.frame(x = factor(c("A", "A", "A", "B", "B")))
x3 <- data.frame(x = factor(c("A", "A", "B", "B", "B", "B")))
xf <- folder(x1, x2, x3)
matddhellinger(xf)
# 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")))
x3 <- data.frame(x = factor(c("A", "A", "B", "B", "B", "B")),
y = factor(c("a", "b", "a", "b", "a", "b")))
xf <- folder(x1, x2, x3)
matddhellinger(xf)
[Package dad version 4.1.2 Index]