Bibliographic Details
| Title: |
STRUCTURAL AND ANALYTICAL PROPERTIES OF PROBABILITY MEASURES INDUCED BY GRAPHS. |
| Authors: |
Artes Jr., Rosalio G.1 rosalioartes@msutawi-tawi.edu.ph, Sappayani, Arsanial E.2 arsappayanial@gmail.com, Kiram, Myrna S.2 myrnasungak@gmail.com, Rasid, Sherna A.3 shernrasid@gmail.com |
| Source: |
Advances & Applications in Discrete Mathematics. May2026, Vol. 43 Issue 4, p483-495. 13p. |
| Subjects: |
Probability measures, Graph theory, Entropy, Matching theory |
| Abstract: |
This paper extends the concept of probability measures induced by graphs by developing a comprehensive structural and analytical framework for probable graphs. A graph-induced probability measure is defined via normalized vertex degrees. It is shown that a graph is probable if and only if its size equals half its order, establishing a direct connection between probabilistic normalization and graph structure. New results include a characterization of probable graphs via average degree, connections with perfect matchings, entropy-based interpretations, and the introduction of a probability generating polynomial. These results provide a deeper understanding of the interplay between graph theory and probability, and open new directions for applications in network analysis and stochastic modeling. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |
