Can LAAFU effects be modeled?

[magnesium]

There's certainly no harm in exploring that.  But since one of his goals is to "(b) consistently replicate these properties [ = 'well-known VMS statistical properties' ] when encrypting a wide range of plaintexts in a well-characterized natural language," I assume he'd prefer to model a system that would reliably produce LAAFU effects when applied to any source text.  

Just wondering: how difficult would it be to adapt the Naibbe approach from a unigram/bigram system to a syllabic "chunk" system?  Might the frequencies of different "chunk" types result naturally in something like the frequency distributions simulated through playing cards?

That is absolutely my preference. My first goal was to achieve something that could replicate word-level properties reliably and then build from there. I don't think it would be difficult at all to adapt the Naibbe approach to a syllabic "chunk" system, as the lengths of the chunks as you have outlined them—1 or 2 letters—are ultimately the single most important thing within the Naibbe scheme. The VMS's word length distributions and entropy strongly suggest that to reliably map something like Latin to Voynichese, a substitution cipher would have to be verbose, such that most tokens in the VMS stand for 1 or 2 plaintext letters. Within the Naibbe cipher, those tokens are randomly formed on a letter-by-letter basis—but by no means do they have to be. A "chunk" adaptation of the Naibbe cipher would essentially equate to a deterministic, nonrandom approach to plaintext respacing.

Even within a syllabic "chunk" system, though, I'm of the opinion that the cipher would need to be homophonic, with multiple valid Voynichese word types mapping to a given plaintext chunk. Otherwise it's hard to get the VMS's observed diversity of word types and frequency-rank distribution.

To add on here, a syllabic "chunk" modification to the Naibbe cipher probably would also help strengthen VMS-like topic detection. In my work to date analyzing Naibbe ciphertexts using TF-IDF, the most diagnostic ciphertext word types of a given plaintext topic are rare word types that encrypt language-dependent or topic-dependent bigrams. For example, when I encrypt a text that is partially Dante's Divine Comedy and partially Latin, rare ways of encrypting "CH" are much more common in the Divine Comedy section (because of Italian words like "che") than in the Latin section. If respacing were not totally random as it is in the current version of the Naibbe cipher, these kinds of syllables might be produced more often and would therefore stack up more quickly.

Non-random reuse of bigram word types would also help explain some mismatches between Voynich B and Naibbe ciphertexts deeper in the frequency-rank distribution, in the words of ranks ~150-500. These words are about 1.5-2x more common within Voynich B than they are in Naibbe ciphertexts. I suspect that this difference would narrow if the Naibbe cipher had some nonrandom line-by-line reuse, based in part on the fact that there's more token autocorrelation at offsets of 1-300 within Voynich B than there is within Naibbe ciphertexts. The way to reuse line-by-line is to preferentially chunk the plaintext so that on line N, you can reuse one of the word types you used in line N-1.