Approximating discrete probability distributions with dependence
trees
C. Chow, и C. Liu. Information Theory, IEEE Transactions on, 14 (3):
462-467(мая 1968)
Аннотация
A method is presented to approximate optimally ann-dimensional discrete
probability distribution by a product of second-order distributions,
or the distribution of the first-order tree dependence. The problem
is to find an optimum set ofn - 1first order dependence relationship
among thenvariables. It is shown that the procedure derived in this
paper yields an approximation of a minimum difference in information.
It is further shown that when this procedure is applied to empirical
observations from an unknown distribution of tree dependence, the
procedure is the maximum-likelihood estimate of the distribution.
%0 Journal Article
%1 Chow1968
%A Chow, C.
%A Liu, C.
%D 1968
%J Information Theory, IEEE Transactions on
%K Approximation Probability Trees functions, methods, null
%N 3
%P 462-467
%T Approximating discrete probability distributions with dependence
trees
%V 14
%X A method is presented to approximate optimally ann-dimensional discrete
probability distribution by a product of second-order distributions,
or the distribution of the first-order tree dependence. The problem
is to find an optimum set ofn - 1first order dependence relationship
among thenvariables. It is shown that the procedure derived in this
paper yields an approximation of a minimum difference in information.
It is further shown that when this procedure is applied to empirical
observations from an unknown distribution of tree dependence, the
procedure is the maximum-likelihood estimate of the distribution.
@article{Chow1968,
abstract = { A method is presented to approximate optimally ann-dimensional discrete
probability distribution by a product of second-order distributions,
or the distribution of the first-order tree dependence. The problem
is to find an optimum set ofn - 1first order dependence relationship
among thenvariables. It is shown that the procedure derived in this
paper yields an approximation of a minimum difference in information.
It is further shown that when this procedure is applied to empirical
observations from an unknown distribution of tree dependence, the
procedure is the maximum-likelihood estimate of the distribution.},
added-at = {2009-09-12T19:19:34.000+0200},
author = {Chow, C. and Liu, C.},
biburl = {https://www.bibsonomy.org/bibtex/238cadeb201c1927dd50a0e742d778c46/mozaher},
file = {:Chow1968.pdf:PDF},
interhash = {a83c0133a570dc207f9633490df82178},
intrahash = {38cadeb201c1927dd50a0e742d778c46},
issn = {0018-9448},
journal = {Information Theory, IEEE Transactions on},
keywords = {Approximation Probability Trees functions, methods, null},
month = May,
number = 3,
owner = {Mozaherul Hoque},
pages = { 462-467},
review = {MWST algorithm},
timestamp = {2009-09-12T19:19:38.000+0200},
title = {Approximating discrete probability distributions with dependence
trees},
volume = 14,
year = 1968
}