entropy.overall: Compares the observed and expected information content of the...

In AlexMielke1988/NetFACS: Network Applications to Facial Communication Data

Description

Establishes how'ordered' the data is: values close to 0 indicate that combinations are highly repetitive and predictable, while values close to 1 indicate that combinations are equiprobable and prediction of future combinations is difficult

Usage

entropy.overall(netfacs.data)

Arguments

netfacs.data

object resulting from netfacs() function

Value

Function returns the ratio of observed entropy/expected entropy. Expected entropy is based on randomization (shuffling the observed elements while maintaining the number of elements per row) and represents the maximum entropy a dataset with the same properties as this one can reach. Ratios closer to 0 are more ordered; ratios closer to 1 are more random.

Examples

### how do angry facial expressions differ from non-angry ones?
data(emotions_set)
angry.face <- netfacs(
  data = emotions_set[[1]],
  condition = emotions_set[[2]]$emotion,
  test.condition = "anger",
  ran.trials = 100,
  combination.size = 2
)

entropy.overall(angry.face)

AlexMielke1988/NetFACS documentation built on Oct. 27, 2020, 4:14 p.m.