Skip to main content
  • 1071 Accesses

Abstract

In the preceding chapter, we saw birth-death processes as a special class of continuous-time Markov chains. Let &#x007X(t)} denote a birth-death process. In Example 4.4, X(t) represents the size of a population at time t. A ‘birth’ increases the size by 1 and a ‘death’ decreases it by 1. However, this is indeed a rich and important class in modeling a variety of phenomena not only in biology but also in, e.g., operations research, demography, economics and engineering. Typical examples of problems that can be formulated as birth-death processes are the following.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 1997 M. Kijima

About this chapter

Cite this chapter

Kijima, M. (1997). Birth—death processes. In: Markov Processes for Stochastic Modeling. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-3132-0_5

Download citation

  • DOI: https://doi.org/10.1007/978-1-4899-3132-0_5

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-412-60660-1

  • Online ISBN: 978-1-4899-3132-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics