From Random Partitions to Self-Similar Processes

Abstract

Nowadays when modeling real-life phenomena, in many areas stochastic methods have become more and more popular in addition to traditional methods based on deterministic ordinary differential equations and partial differential equations. Here modeling means to propose a mathematical model that could reproduce complex behavior reflexed by empirical data. Broadly speaking, stochastic modeling usually consists of twosteps. The first is to construct a probability model that represent certain important features of the phenomena of interest. In this step, the features of interest, or more essentially the underlying dynamics, are determined by a set of parameters of the model constructed.

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Document Details

Document Type
Technical Report
Publication Date
Dec 19, 2019
Accession Number
AD1097148

Entities

People

  • Yizao Wang

Organizations

  • University of Cincinnati

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Applied Mathematics
  • Brownian Motion
  • Computational Science
  • Differential Equations
  • Gaussian Processes
  • Information Science
  • Markov Processes
  • Partial Differential Equations
  • Phase Transformations
  • Probabilistic Models
  • Probability
  • Random Variables
  • Random Walk
  • Simulations
  • Statistics
  • Stochastic Processes
  • Theorems

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Educational Psychology
  • Mathematical Modeling and Probability Theory.