05-09-2025, 12:49 PM
(This post was last modified: 05-09-2025, 12:50 PM by quimqu.
Edit Reason: tipo
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I had used the standard Pearson correlation on word length vs. next word’s length, which gave me a slightly negative value (alternating tendency). I now see that Nablator uses a binary measure (short vs. long compared to the mean). These are two different definitions of autocorrelation, so it makes sense that results diverge. Both are interesting because they highlight different aspects of Voynichese rhythm.
I think it is true that with lag-1 we are only looking at short-term autocorrelation. Several studies indicate that natural languages also tend to show slightly negative autocorrelation at this short distance — meaning that long words are often followed by short ones, and vice versa. At longer ranges, however, the correlation tends to become slightly positive in natural languages. From this perspective, it is actually good news that the Voynich also shows negative short-term autocorrelation, because that is in line with what we would expect from natural language behavior.
Anyway, I agree with Marco's opinion that this shoud go to another thread. Sorry.
I think it is true that with lag-1 we are only looking at short-term autocorrelation. Several studies indicate that natural languages also tend to show slightly negative autocorrelation at this short distance — meaning that long words are often followed by short ones, and vice versa. At longer ranges, however, the correlation tends to become slightly positive in natural languages. From this perspective, it is actually good news that the Voynich also shows negative short-term autocorrelation, because that is in line with what we would expect from natural language behavior.
Anyway, I agree with Marco's opinion that this shoud go to another thread. Sorry.