The most anomalous, and therefore indicative value is that of h2, which tells about the 'unpredictability' of how characters combine, though it has to be seen in relation with h1, which is the unpredictability of single characters.
The Currier alphabet is the most 'compressed' we have, and gives the highest entropy. Taking some values from this page:
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Currier and Eva transcriptions of herbal A text have almost identical h1 values of 3.8, though Currier has 36 symbols and Eva only 26.
The h2 in Eva is 1.99 and in Currier 2.32.
For a Latin text, h1 and h2 values are 4.0 and 3.3 respectively.
This clearly shows the magnitude of our problem.
By the way, and importantly: a compression algorithm increases the entropy because during the compression there is no loss of information.
The entropy per character increases because the same amount of information is distributed over fewer characters.
Whatever the Voynich author did that ultimately reduced the entropy may have been a spreading of information over more characters, but it could also have been a reduction (loss) of information.
The Currier alphabet is the most 'compressed' we have, and gives the highest entropy. Taking some values from this page:
You are not allowed to view links. Register or Login to view.
Currier and Eva transcriptions of herbal A text have almost identical h1 values of 3.8, though Currier has 36 symbols and Eva only 26.
The h2 in Eva is 1.99 and in Currier 2.32.
For a Latin text, h1 and h2 values are 4.0 and 3.3 respectively.
This clearly shows the magnitude of our problem.
By the way, and importantly: a compression algorithm increases the entropy because during the compression there is no loss of information.
The entropy per character increases because the same amount of information is distributed over fewer characters.
Whatever the Voynich author did that ultimately reduced the entropy may have been a spreading of information over more characters, but it could also have been a reduction (loss) of information.