Voynich words evolve over a linear sequence

[npcompl33t]

Thank you npcompl33t, I find the subject very interesting!

In my opinion, there's much wasted space in the images in post #1: if empty horizontal space could be removed, maybe the graphs would be easier to read.

The horizontal space there is relevant, they are spaced proportionally to the identified time sequence in the previous post. So it shows the approximate relative time between each section.  I can post them with equal separation if that would help, its an easy toggle already built into the app.

Also, I would prefer to see rules listed and discussed in the forum post, rather than at an external page that I expect will change in the future.

This is fair, I want to be clear I am not claiming this rule-set is comprehensive or entirely correct. I think it shows that certain specific transformations can move the frequency distribution, but I am still researching and evaluating the rules and I'm not prepared to defend them all individually yet. The intention here was to show that this is possible and a worthwhile avenue for research, not to claim these rules are the canonical set. If i was making the later claim, i would absolutely put them here on the forum. I can definitely post a list of which transformations i am using above if you think that is helpful, i just want to be clear that I am not arguing they are comprehensive.

I am not sure I understand what is being said here. "replacement" is a theory, one can see the same phenomenon as “gradually vanishing”. It seems you are drawing an inference from an assumption that may or may not be correct.

Your point strikes at the core of the matter, which is I don't think this has been adequately discussed. All previous debate has focused on the existence of the gradient, not on what types of features might distinguish gibberish self copying vs some type of semantic information presrerving transformation,. 

My point was more that both semantic preserving drift and meaningless copying should manifest differently. If the text encodes semantic meaning, then any transformations ultimately need to preserve information. I would greatly appreciate a discussion around this.

If chol were to vanish without a candidate replacement occurring at roughly the same frequency, that would be strong evidence for self citation or gibberish. Chol ultimately means nothing, so the scribes aren't concerned with making sure its descendants occur at roughly the same rate. 

The other explanation would be Lexical Replacement, where one word gradually replaces another. It happens all the time in real languages. These transformations appear to preserve frequencies in the above example, which is not necessary for self-citation but is to preserve semantic meaning. 

EDIT: Maybe a detailed discussion of a limited set of words, like You are not allowed to view links. Register or Login to view., would also make the theory easier to understand.

i think getting into the specifics is going to be critical to resolve this. In torstens theory, he has both cheo and chey as a part of chol's transformation. I do not think that makes sense. It makes more sense , in my opinion for chy -> chey. They appear to mostly preserve frequency mass when calculated this way. The difference here is extremely important, because failure to preserve information or losing words outright in my opinion would be strong evidence against semantic meaning. 

More broadly, i think collectively discussing what sorts of markers would help distinguish semantic meaning vs self citation within the context of the gradient would be extremely valuable.