Maximum Likelihood Estimation in the Birth-and-Death Process

Abstract

Maximum likelihood estimation of the parameters lambda and mu of a simple (linear) birth-and-death process observed continuously over a fixed time interval is studied. Asymptotic distributions for large initial populations and for large periods of observation are derived and some nonstandard results appear. The related problem of estimation from the discrete skeleton of the process is also discussed.

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Document Details

Document Type
Technical Report
Publication Date
Nov 28, 1973
Accession Number
AD0775243

Entities

People

  • Niels Keiding

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Confidence Limits
  • Data Science
  • Estimators
  • Information Science
  • Intervals
  • Markov Processes
  • Maximum Likelihood Estimation
  • Normality
  • Probability
  • Random Variables
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Inference
  • Statistics
  • Stochastic Processes
  • Time Intervals

Fields of Study

  • Mathematics

Readers

  • Analytical Mechanics
  • Chemistry (specifically Chemical Fluorescence)
  • Regression Analysis.