The Mathematical Theory of Information: New results
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As an answer to the question "Can the selection of information measure influence the ordering of messages according to informativity?", a new theorem was found.
My book, The Mathematical Theory of Information presents a measure of the information B gives about A, ent_alpha(B@A), derived from Rényi's generalization of Shannon's entropy. The range of alpha was given as 0<=alpha<1, and it was proved that ent_alpha(B@A) conforms to the Law of Diminishing Information.
Then Jan Hajek pointed out in a question that the literature puts no upper limit to alpha. I guessed it could be proved alpha > 1 would be allowed. Then Hajek came back with a paper Renyi's disinformation presenting the result that there are values of alpha > 2 leading to a violation of the Law of Diminishing Information.
To sort this out I had to purchase Mathematica, as my normal pencil-and-paper methods would have been too cumbersome. An experienced user will find my handling of the program lacking elegance. I muddled trough somehow, even when the program refused to recognize that 0^2 = 0 etc.
The paper Rényi Rate Formula (Mathematica/MathReader file, 620 kB) explores ent_alpha(B@A) and finds the allowed range to be 0<=alpha<=2 (where alpha = 1 produces Shannons entropy as a limit).
Hajek also points out in Renyi's disinformation that ent_alpha(B@A) is asymmetric, ent_alpha(B@A) may differ from ent_alpha(A@B). In the paper Symmetric Rényi (Mathematica/MathReader file, 440 kB), a symmetric measure of the information B gives about A, ent_alpha(B;A) is constructed. That is, ent_alpha(B;A) = ent_alpha(A;B). The allowed range was found to be 0<=alpha<=1 (where alpha = 1 produces Shannons entropy as a limit).
Contact: jankahre (at) hotmail.com