Editing Joint probability distribution (section)

===Joint distribution for conditionally dependent variables===
If a subset <math>A</math> of the variables <math>X_1,\cdots,X_n</math> is [[conditional dependence|conditionally dependent]] given another subset <math>B</math> of these variables, then the probability mass function of the joint distribution is <math>\mathrm{P}(X_1,\ldots,X_n)</math>.  <math>\mathrm{P}(X_1,\ldots,X_n)</math> is equal to <math>P(B)\cdot P(A\mid B)</math>. Therefore, it can be efficiently represented by the lower-dimensional probability distributions <math>P(B)</math> and <math>P(A\mid B)</math>. Such conditional independence relations can be represented with a [[Bayesian network]] or [[Copula (probability theory)|copula functions]].