Sentence examples for represent random variables from inspiring English sources

We present a reformulation of the Bayesian approach to inverse problems, that seeks to accelerate Bayesian inference by using polynomial chaos (PC) expansions to represent random variables.

Vertices represent random variables and edges represent direct correlation between them.

because they represent random variables that only take non-negative values (as in (1), where a distance is involved).

Their nodes represent random variables (discrete or continuous) and the edges represent conditional dependencies, forming a directed acyclic graph.

Here we suggest a model, a simple generalization of a Bayesian network, where both arcs and nodes represent random variables.

The nodes represent random variables and the arcs represent conditional probabilistic dependency between nodes, where the distribution of each node is dependent on its parent nodes but conditionally independent of all other nodes.

These preparations include the derivation of sophisticated stochastic representations of the uniformly distributed random vectors as presented in Sections 4.1.1 and 4.2.1 as well as non-trivial distributional considerations for the representing random variables sketched also there.

Bayesian networks can be described as a directed acyclic graph with nodes representing random variables or genes and directed edges representing the relationships between the nodes [ 5, 10].

For the model to remain consistent, the graph structure, with nodes representing random variables and directed edges representing conditional probability relationships between them, must be acyclic.

On one hand, FN derive from annotations representing random variables that refer implicitly to an exhaustive set of alternative states, like 'present'/'absent', 'active'/'inactive' or a richer set of values.

Let M x ), I(x ) and N(x ) be random variables representing the measured data, noise-free data and speckle noise of unknown distribution at pixel x respectively.