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Estimating Parameters of a Directed Weighted Graph Model with Beta-Distributed Edge-Weights

  • M. BollaEmail author
  • J. Mala
  • A. Elbanna
Article

We introduce a directed, weighted random graph model, where the edge-weights are independent and beta distributed with parameters depending on their endpoints. We will show that the row- and column-sums of the transformed edge-weight matrix are sufficient statistics for the parameters, and use the theory of exponential families to prove that the ML estimate of the parameters exists and is unique. Then an algorithm to find this estimate is introduced together with convergence proof that uses properties of the digamma function. Simulation results and applications are also presented.

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of MathematicsBudapest University of Technology and EconomicsBudapestHungary
  2. 2.Institute of MathematicsELTE Eötvös Loránd UniversityBudapestHungary
  3. 3.Faculty of Science, Mathenmatics DepartmentTanta UniversityTantaEgypt

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