Compute Kullback-Leibler symmetric distance.
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X |
An input data matrix. |
Y |
An input data matrix. |
k |
The maximum number of nearest neighbors to search. The default value is set to 10. |
algorithm |
nearest neighbor search algorithm. |
Kullback-Leibler distance is the sum of divergence q(x)
from p(x)
and p(x)
from q(x)
.
KL.*
versions return distances from C
code to R
but KLx.*
do not.
Return the Kullback-Leibler distance between X
and Y
.
Shengqiao Li. To report any bugs or suggestions please email: shli@stat.wvu.edu.
S. Boltz, E. Debreuve and M. Barlaud (2007). “kNN-based high-dimensional Kullback-Leibler distance for tracking”. Image Analysis for Multimedia Interactive Services, 2007. WIAMIS '07. Eighth International Workshop on.
S. Boltz, E. Debreuve and M. Barlaud (2009). “High-dimensional statistical measure for region-of-interest tracking”. Trans. Img. Proc., 18:6, 1266–1283.
KL.divergence
.
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