What question did this study set out to answer?

The research aims to present algorithms for estimating Shannon entropies of symbol sequences and their efficiency in coding.

Estimating the information content of symbol sequences and efficient codes

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Randomized trial estimates Shannon entropies in symbol sequences, suggesting optimal coding for natural languages.

The research aims to present algorithms for estimating Shannon entropies of symbol sequences and their efficiency in coding.
Developed variants of algorithms related to the Lempel-Ziv algorithm and Hausdorff dimension calculations.
Analyzed average storage and running times as functions of sequence length N and Nlog N.
Demonstrated application of algorithms using written English as a case study.
Algorithms show optimal performance for sequences with strong long-range correlations, like natural languages.
Storage and running times increase predictively with sequence length N and Nlog N.
Application case in written English illustrates effective use for practical coding.

Peter Grassberger (1989) studied this question.

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