THE USE OF THE HYPERGEOMETRIC FUNCTION AS PART OF BAYESIAN ESTIMATION IN A TWO STATE MARKOV PROCESS,

Abstract

A special case of Bayesian estimation in Markov processes is considered. We consider a two state process where one transition probability is known exactly, while the other is assumed Beta distributed. Under these conditions the expected values of the steady state probabilities are obtained through the use of the hypergeometric function, a mathematical function heretofore encountered only in an entirely different area of applied mathematics. Knowing the expected values of the steady state probabilities enables us to place the process considered into a statistical decision framework. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1964
Accession Number
AD0428852

Entities

People

  • Edward A. Silver

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Applied Mathematics
  • Complex Systems
  • Hypergeometric Functions
  • Markov Processes
  • Mathematics
  • Probability
  • Random Variables
  • Steady State
  • Stochastic Processes
  • Transitions

Fields of Study

  • Mathematics

Readers

  • Calculus or Mathematical Analysis
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms