entropy: Entropy

In hlennon/LCTMtools: Latent Class Trajectory Models: Tools for checking adequacy

Entropy

Description

A global measure of uncertainty with values close to zero implying a good model. Entropy is a global measure of classification uncertainty, which takes into account all N × K posterior probabilities. The entropy of a model is defined as which takes values from [0,infinity), with higher values indicating a larger amount of uncertainty. Entropy values closest to 0 correspond to models with least classification uncertainty.

Usage

entropy(p)

Arguments

p	is the posterior probabilities of assignment of dimensions, K columns and N rows

Value

Entropy value between (0, infinity)

Examples

## Not run: entropy(p)

hlennon/LCTMtools documentation built on Dec. 6, 2022, 3:04 a.m.