List of algorithms from NIST 800-90B, Schürmann and Grassberger, Hutter Prize entries and Gupta and Agarwal deep learning techniques for entropy measurement in the general (correlated/ non-IID) case:-
List (incomplete) of entropy measuring algorithms:-
Most Common Value Estimate.
Longest Repeated Substring (LRS) Estimate.
Multi Most Common in Window Prediction Estimate.
Lag Prediction Estimate.
MultiMMC Prediction Estimate.
LZ78Y Prediction Estimate.
Ziv - Lempel.
Gambling & suffix trees.
Bayesian probability estimation.
Superposition of probabilities.
Global probability estimates.
Hutter Prize entries.
Ouija technique for asking Shannon himself.
And a shed load of deep learning/artificial intelligence techniques…
And there are others still, with a significant proportion based around compression theory. So what to do?