I am not familiar with what kind of entropy measures are adopted in linguistics.
As long as the Voynich manuscript is concerned, in my personal opinion, it might need to be determined how to handle the text with the context modifiers before applying any statistical measures.
I mean the "context modifiers" by referring to those content bearing words introduced by Montemurro and Zanette(2013) from the University of Manchester.
I called those content bearing words as skeletons in my article and non-content bearing words as fleshes.
By definition, a skeleton is Voynich letter(s) that repeat themselves in the trailing text.
In the Voynich manuscript, those skeletons mostly are identified as prefixes.
Skeletons consists of one or more Voynich letters.
If Voynich words are categorized, they can be grouped into several categories.
Category 1. A word is consisted of skeleton and flesh.
Category 2. Skeletons. The skeleton words separated from the words in the Category 1.
Category 2a. Cascaded skeleton. With two consecutive words in the form of AB BC where B is a skeleton, B is called a cascaded skeleton.
Category 2b. Delimiting skeleton. When two words are used to comprise a text segment in the form of AB ~ A where A is a skeleton, A is called a delimiting skeleton.
Category 3. Fleshes. The flesh words separated from the words in the Category 1.
Category 4. Standalone flesh word. A word does not contain any skeleton in it.
In the viewpoint of the context change or the shift in topics, skeletons are regarded as context modifiers.
Context modifiers have their meaning and can be used standalone in the text.
When they are attached to fleshes, it does not make up new words, but just modifies the context of flesh words.
For example, I divided the f80r text, except those captions on the top, into 13 segments and the first segment S1 consists of 14 words.
[Category 1. The text in S1 in its original form (as it is, from the reference site)]
pdol fshedy q*polkain octhor okchdy qokeedy qo*cheol ol*oiin y darshey dykshy olotchedy qokai*n qotain
[The text in S1 in a formatted style. (I mean "formatted" by using line breaks and indentations. The purpose of formatting is to align skeletons at the same indentation position.)]
L1: pdol fshedy q*polkain octhor
L2: okchdy
L3: qokeedy
L4: qo*cheol ol*oiin y darshey
L5: dykshy
L6: olotchedy
L7: qokai*n
L8: qotain
At the first indentation depth, the skeleton 'qo' can be identified from L1, L3, L4, L7, L8. (I assumed that 'q*' in L1 would be 'qo'.)
At the second indentation depth, two skeletons are identified and they are 'o-' from L1 & 2 and 'ol' or 'olo' if 'ol*' is actually 'olo'. If not, the skeleton will be just 'ol'.
At the third indentation depth, one skeleton 'd' is identified.
I categorize the leading two words 'pdol fshedy' as a title to S1 and both words are flesh words without skeleton.
As it can be seen, the categorization of skeleton and flesh is purely theoretical, produced purely based on a pattern match.
[Category 2: Skeletons only, 4 in total in S1]
'qo', 'o', 'olo', 'd'
[Category 3: Fleshes attached to skeletons, 12 in total]
L1: polkain cthor (without 'qo' and 'o')
L2: kchdy (w/o 'o')
L3: keedy (w/o 'o')
L4: cheol oiin y arshey (w/o 'qo', 'olo', 'd')
L5: ykshy (w/o 'd')
L6: tchedy (w/o 'olo')
L7: kai*n (w/o 'qo')
L8: tain (w/o 'qo')
[Category 4: Fleshes with no skeletons, 2 in total]
L1: pdol fshedy
When the original Voynich words are grouped into Categories 2 to 4, the categorization will change the data set of input words.
The statistical characteristics of those words after categorization definitely are different from the statistical characteristics of original Voynich words.
It means that any entropy calculation taken on categorized words may produce different results than those taken on original words.