Sample entropy vs approximate entropy

1. How do you calculate entropy of a sample?
2. What is cross sample entropy?
3. Can approximate entropy be negative?
4. What is embedding dimension in sample entropy?

How do you calculate entropy of a sample?

If X can take the values x 1 , … , x n and p ( x ) is the probability associated with those values given x ∈ X , entropy is defined as: H ( X ) = − ∑ x ∈ X p ( x ) log p ( x ) .

What is cross sample entropy?

Cross-sample entropy (CSE) allows to analyze the association level between two time series that are not necessarily stationary. The current criteria to estimate the CSE are based on the normality assumption, but this condition is not necessarily satisfied in reality.

Can approximate entropy be negative?

Approximate entropy should not be negative because the pdf and the conditional distribution should normally integrate to 1. The Lagrangian constants are also non negative. Negative entropy is meaningless. Entropy should not be less than 0.

What is embedding dimension in sample entropy?

Details. The sample entropy is computed using: hq(m,r) = log(Cq(m,r)/Cq(m+1,r)), where m is the embedding dimension and r is the radius of the neighbourhood.