ddjeffreys {dad} | R Documentation |
Divergence between probability distributions of discrete variables given samples
Description
jeffreys's divergence (symmetrized Kullback-Leibler divergence) between two multivariate (q > 1
) or univariate (q = 1
) discrete probability distributions, estimated from samples.
Usage
ddjeffreys(x1, x2)
Arguments
x1 , x2 |
vectors or data frames of If they are data frames and have not the same column names, there is a warning. |
Details
Let p_1
and p_2
denote the estimated probability distributions of the discrete samples x_1
and x_2
. The jeffreys's divergence between the discrete probability distributions of the samples are computed using the ddjeffreyspar
function.
Value
The divergence between the two probability distributions.
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
ddjeffreyspar
: Jeffrey's distances between two discrete distributions, given the probabilities on their common support.
Other distances: ddchisqsym
, ddhellinger
, ddjensen
, ddlp
.
Examples
# Example 1
x1 <- c("A", "A", "B", "B")
x2 <- c("A", "A", "A", "B", "B")
ddjeffreys(x1, x2)
# Example 2 (Its value can be infinity -Inf-)
x1 <- c("A", "A", "B", "C")
x2 <- c("A", "A", "A", "B", "B")
ddjeffreys(x1, x2)
# Example 3
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")))
ddjeffreys(x1, x2)