An explanation of the Voynich Manuscript text

[DonaldFisk]

I carried out this test, and confirmed that words in the manuscript are independent of the previous word (see You are not allowed to view links. Register or Login to view.).   The mean frequency of word pairs was very close to the expected probability (the product of the probabilities of the two words considered separately), but the frequency's variance was very close to the square of the mean (i.e. a Gamma distribution, in my generated text it was a Poisson distribution), suggesting that the mechanism I initially suggested for deciding on transition paths, and only that, was wrong.   As far as I know, no one had spotted this before.

I'm sorry but this is completely inconclusive.

Your figure 1 shows a strong deviation from randomness.
Still, also that is not conclusive in the other direction.

What completely lacks is evidence (metrics) for:
- what should be the statistical behaviour of a meaningful text
- how much variation there would be in this

The analysis is based on the assumption that every word type in the Voynich MS should consistently represent the same word in some plain text. This is not at all certain.
If the Voynich MS text includes null characters, all word combination statistics are completely thrown off.

There was a thread here in the voynich.ninja where there was a strong indication that the repeating sequence statistics in the MS are not that different from a known plain text.
(Of course also that is not conclusive for the same reason: "not that different" is not sufficiently defined).

My summary is:
- there are indications that the text could be meaningful
- there are indications that the text could be meaningless
Both are still inconclusive.
Some papers concentrate more on one or the other, but other papers do state both.

There are different kinds of random: Gaussian, Poisson, etc.   Figure 2 and Figure 4 show that the distribution mean is the same as you'd get by chance, and that the distribution variance is the square of the mean, i.e. it behaves like a Gamma distribution.

However, Figure 6 shows that there's at least one glyph pair (final y, initial qo) which occurs roughly twice as often.   There must actually be more than one, to prevent the distribution becoming skewed.   To avoid complexity, I'd now work on the assumption that  the initial glyph always depends on the final glyph of the previous word.   That came as a surprise to me, but it doesn't prove meaning, and it might (I haven't checked) explain the Gamma distribution.   It can easily be accommodated by my state transition model.

Yes, it's worth checking texts in other languages, to see how their distributions differ from chance, though someone will no doubt point out that I haven't checked Tocharian B.

I think what's needed, as people are divided into three camps (unencrypted, encrypted, meaningless; and even within those camps there's disagreement) are tests agreed in advance and validated by statisticians, which are considered acceptable by everyone as evidence.

And there has to come a point where you say, "This is enough evidence, I think X is true," or even, "Even though this clearly isn't enough evidence, I think X is probably true," but still be prepared to change your position if new evidence arrives.   That point has, for me, been reached.   I think the text is probably, bordering on almost certainly, meaningless, generated by a stochastic process.   I haven't worked out all the details.    But if someone is ever able to provide a translation which isn't nonsense, I'll change my mind.   So far, they haven't.