View source: R/matddjeffreys.R
matddjeffreys | R Documentation |
Computes the matrix of Jeffreys divergences between several multivariate or univariate discrete probability distributions, estimated from samples.
matddjeffreys(x)
x |
object of class |
Positive symmetric matrix whose order is equal to the number of data frames (or distributions), consisting of the pairwise Jeffreys divergences between the distributions.
Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Sabine Demotes-Mainard
Deza, M.M. and Dezaz E. (2013). Encyclopedia of distances. Springer.
ddjeffreys
.
matddjeffreyspar
for discrete probability densities, given the probabilities on the same support.
# 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)
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