kullback_leibler_divergence {abdiv} | R Documentation |
Kullback-Leibler divergence
kullback_leibler_divergence(x, y)
x, y |
Numeric vectors representing probabilities |
Kullback-Leibler divergence is a non-symmetric measure of difference between two probability vectors. In general, KL(x, y) is not equal to KL(y, x).
Because this measure is defined for probabilities, the vectors x and y are normalized in the function so they sum to 1.
The Kullback-Leibler divergence between x
and y
. We
adopt the following conventions if elements of x
or y
are
zero: 0 \log (0 / y_i) = 0, 0 \log (0 / 0) = 0, and
x_i \log (x_i / 0) = ∞. As a result, if elements of x
are
zero, they do not contribute to the sum. If elements of y
are zero
where x
is nonzero, the result will be Inf
. If either
x
or y
sum to zero, we are not able to compute the
proportions, and we return NaN
.