stochasticComplexity: Stochastic Complexity for Multinomials

In SCCI: Stochastic Complexity-Based Conditional Independence Test for Discrete Data

Description

Efficient implementation of the exact computation of stochastic complexity for multinomials (Silander et al. 2008) for data over a discrete random variable X.

Usage

stochasticComplexity(x)	

Arguments

x	A discrete vector.

References

Tomi Silander, Teemu Roos, Petri Kontkanen and Petri Myllymäki; Factorized Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures, Proceedings of the 4th European Workshop on Probabilistic Graphical Models, 2008

Examples

set.seed(1)
x = round((runif(1000, min=0, max=5)))
stochasticComplexity(x=x)	## 2544.698

SCCI documentation built on June 4, 2019, 5:03 p.m.