The {8am} strategy

[kckluge]

<>RFD calculations. Is it:

Code:

abs(Freq in VMS- Freq - OTHER) for each term / number of terms * 100?

<>Why are you (usually) choosing to count just the frequency in the herbal section vs the entire document and how do you choose which documents to "map" to?

Thank you for your interest in what I have called the {8am] strategy.



What I have called the average absolute frequency difference (AFD) is a metric for ranking or prioritising various alternative transliterations of the Voynich manuscript (currently numbering about thirty-seven), all of my own devising and all based on Glen Claston’s v101. All of my transliterations differ from v101 in one significant respect: namely my assumption that Claston’s {4o} is a single glyph. I have used the Unicode symbol ④ to designate this glyph. 


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I calculate the absolute frequency differences for all the available letters, or all the available glyphs (whichever is less). The average absolute frequency difference is simply the average of all the individual frequency differences.



The lower the AFD, the more closely the “shape” of the transliteration approximates to the “shape” of the medieval Italian language; and therefore (to my mind) the more encouragement for the hypothesis that the transliteration represents the medieval Italian language. I don't apply any cut-off for the AFD.

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So you have a discrete probability distribution and you want to measure its similarity to N other discrete probability distributions, and the similarity measure you've chosen is AFD. What other metrics to do that did you look at, and why did you pick the AFD over those other alternatives?