PAPER TITLE: Introducing The Anagram Distance Statistic, Ã, A Quantifier of Lexical Proximity For Base-10 o-SSI And Any Arbitrary Length Ordered Sequences, Its Relevance And Proposed Applications in Computer Science, Engineering And Mathematical Statistics

TAGS: #Research #Physics #InformationTheory #RandomNumbers #InformationGenerators #Entropy #Cybernetics #Statistics #OrderedSequences #ComputerScience #ProfJWL #Nuchwezi

TO CITE:

Lutalo, Joseph Willrich. “Introducing The Anagram Distance Statistic, Ã, A Quantifier of Lexical Proximity For Base-10 o-SSI And Any Arbitrary Length Ordered Sequences, Its Relevance And Proposed Applications in Computer Science, Engineering And Mathematical Statistics.” Academia, FigShare, 2025. https://doi.org/10.6084/m9.figshare.29402363

PAPER TITLE: Introducing The Anagram Distance Statistic, Ã, A Quantifier of Lexical Proximity For Base-10 o-SSI And Any Arbitrary Length Ordered Sequences, Its Relevance And Proposed Applications in Computer Science, Engineering And Mathematical Statistics

ABSTRACT:
While studying various permutations of the base-10 natural symbol set identity (n-SSI)-technically the root of base-10 orthogonal symbol set identities (o-SSI), we have come to realize that there is a simple statistical measure that could be used to quantitatively express how different any two base-10 o-SSI are from the n-SSI. By extending this analysis we have found that we can likewise quantify how different or far apart-in terms of positional order, any two o-SSI expressions are from each other. This idea has then been generalized so that we can use it to statistically test how much disorder (or entropy) a string of a given length has relative to some other reference ordered sequence of similar symbols with finite length, via the Anagram Distance, Ã(•) measure and associated test. New definitions and some new theorems were likewise developed and have been rigorously presented. We conclude by using this measure and the presented o-SSI analysis method to demonstrate several practically relevant problems and their potential solutions, across disciplines such as computer science (in cryptography and information security), the engineering of intelligent systems (in cybernetics and aircraft flight control systems) and in mathematical statistics (in statistical distance measures and goodness-of-fit tests). But this is not the only way this useful statistical measure and associated theory might be applied. Interesting research problems relating to this newly developed entropy measure have been proposed or hinted at, and all this work meant to offer a fundamental theoretical basis for new solutions (or solution methods) to old and new mathematical science problems across many disciplines, domains and fields.

KEYWORDS: Foundations, Entropy Sources, Ordered Sequences, Chaos, Statistical Measures, Intelligent Systems

ABOUT PAPER: This research further advances earlier work concerning information expressions and number sequence transformations as part of random number generator research by Joseph W. Lutalo at his private Nuchwezi Research laboratory. It introduces a new theory, ADT, Anagram Distance Theory, with general applications not only in computer science - his original focus area, but also in mathematical statistics and the mathematical sciences in general, especially those dealing with matters around entropy, ordered sequences and statistic distance measures.

TAGS: #Research #Physics #InformationTheory #RandomNumbers #InformationGenerators #Entropy #Cybernetics #Statistics #OrderedSequences #ComputerScience #ProfJWL #Nuchwezi

TO CITE:

Lutalo, Joseph Willrich. “Introducing The Anagram Distance Statistic, Ã, A Quantifier of Lexical Proximity For Base-10 o-SSI And Any Arbitrary Length Ordered Sequences, Its Relevance And Proposed Applications in Computer Science, Engineering And Mathematical Statistics.” Academia, FigShare, 2025. https://doi.org/10.6084/m9.figshare.29402363

Introducing ADT: Anagram Distance Theory #research & necessary #activism

IN BRIEF: https://doi.org/10.6084/m9.figshare.29424710

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---[THE CALL]:

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Nuchwezi Research