Conditional Independences among Four Random Variables Ii
ثبت نشده
چکیده
Numerous new properties of stochastic conditional independence are introduced. They are aimed, together with two surprisingly trivial examples, at a further reduction of the problem of probabilistic representability for four{element sets, i.e. of the problem which conditional independences within a system of four random variables can occur simultaneously. Proofs are based on fundamental properties of conditional independence and, in discrete case, on use of I{divergence and algebraic manipulations with marginal probabilities. A duality question is answered in negative. 3
منابع مشابه
Conditional Independences among Four Random Variables I
The conditional independences within a system of four discrete random variables are studied simultaneously. The problem where independences can occur at the same time, called the problem of probabilistic representability, is attacked by an analysis of cones of polymatroids. New results on the cone of all polymatroids satisfying Ingleton inequalities imply a substantial reduction of the problem ...
متن کاملConditional Independences among Four Random Variables 2
The conditional independences within a system of four discrete random variables are studied simultaneously. The problem where independences can occur at the same time, called the problem of probabilistic representability, is attacked by an analysis of cones of polymatroids. New results on the cone of all polymatroids satisfying Ingleton inequalities imply a substantial reduction of the problem ...
متن کاملOn Gaussian conditional independence structures
The simultaneous occurrence of conditional independences among subvectors of a regular Gaussian vector is examined. All configurations of the conditional independences within four jointly regular Gaussian variables are found and completely characterized in terms of implications involving conditional independence statements. The statements induced by the separation in any simple graph are shown ...
متن کاملDuality between faithfulness assumptions in Graphical models
In this paper we analyze the duality between two faithfulness assumptions that can be defined on a given multivariate probability distribution of a set of random variables. The first pertains to faithfulness to its concentration graph and the second pertains to faithfulness to its covariance graph. The vertices in both these graphs are in a oneto-one correspondence with the set of variables in ...
متن کاملMarkov random fields factorization with context-specific independences
Markov random fields provide a compact representation of joint probability distributions by representing its independence properties in an undirected graph. The well-known Hammersley-Clifford theorem uses these conditional independences to factorize a Gibbs distribution into a set of factors. However, an important issue of using a graph to represent independences is that it cannot encode some t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1995