Translator Disclaimer
June 2015 On binomial observations of continuous-time Markovian population models
N. G. Bean, R. Elliott, A. Eshragh, J. V. Ross
Author Affiliations +
J. Appl. Probab. 52(2): 457-472 (June 2015). DOI: 10.1239/jap/1437658609

Abstract

In this paper we consider a class of stochastic processes based on binomial observations of continuous-time, Markovian population models. We derive the conditional probability mass function of the next binomial observation given a set of binomial observations. For this purpose, we first find the conditional probability mass function of the underlying continuous-time Markovian population model, given a set of binomial observations, by exploiting a conditional Bayes' theorem from filtering, and then use the law of total probability to find the former. This result paves the way for further study of the stochastic process introduced by the binomial observations. We utilize our results to show that binomial observations of the simple birth process are non-Markovian.

Citation

Download Citation

N. G. Bean. R. Elliott. A. Eshragh. J. V. Ross. "On binomial observations of continuous-time Markovian population models." J. Appl. Probab. 52 (2) 457 - 472, June 2015. https://doi.org/10.1239/jap/1437658609

Information

Published: June 2015
First available in Project Euclid: 23 July 2015

zbMATH: 1323.60101
MathSciNet: MR3372086
Digital Object Identifier: 10.1239/jap/1437658609

Subjects:
Primary: 60J27
Secondary: 60J80, 62M09, 62M20

Rights: Copyright © 2015 Applied Probability Trust

JOURNAL ARTICLE
16 PAGES

This article is only available to subscribers.
It is not available for individual sale.
+ SAVE TO MY LIBRARY

SHARE
Vol.52 • No. 2 • June 2015
Back to Top