normEntropy: Theoretical value of the entropy for the multivariate...

In EntropyMCMC: MCMC Simulation and Convergence Evaluation using Entropy and Kullback-Leibler Divergence Estimation

Description

This function computes the entropy E_{f} [\log(f)] of the density of the multivariate gaussian, with parameters in a list, as it is the case for MCMC target density parameters. This function is used mostly for benchmarking entropy estimation performed by the package (using, e.g., the iid algorithm IID_norm).

Usage

normEntropy(target_param)

Arguments

target_param

A list of two elements: the mean target_param$mean and the covariance matrix target_param$v.

Value

The entropy of the Gaussian with these parameters.

Author(s)

Didier Chauveau.

Examples

d=2 # model dimension
mu=rep(0,d); v = diag(d) # mean and variance
target_param = list(mean=mu, v=v) # parameters
normEntropy(target_param) # the entropy

EntropyMCMC documentation built on May 2, 2019, 6:43 a.m.