Skip to main content

Renewal Processes

  • Chapter
Probability Theory

Part of the book series: Universitext ((UTX))

  • 181k Accesses

Abstract

This is the first chapter in the book to deal with random processes in continuous time, namely, with the so-called renewal processes. Section 10.1 establishes the basic terminology and proves the integral renewal theorem in the case of non-identically distributed random variables. The classical Key Renewal Theorem in the arithmetic case is proved in Sect. 10.2, including its extension to the case where random variables can assume negative values. The limiting behaviour of the excess and defect of a random walk at a growing level is established in Sect. 10.3. Then these results are extended to the non-arithmetic case in Sect. 10.4. Section 10.5 is devoted to the Law of Large Numbers and the Central Limit Theorem for renewal processes. It also contains the proofs of these laws for the maxima of sums of independent non-identically distributed random variables that can take values of both signs, and a local limit theorem for the first hitting time of a growing level. The chapter ends with Sect. 10.6 introducing generalised (compound) renewal processes and establishing for them the Central Limit Theorem, in both integral and integro-local forms.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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

Notes

  1. 1.

    That is, the sums \(n^{-1} \sum_{k} \underline{g}_{\,k}\) and \(n^{-1} \sum_{k} \overline{g}_{k}\) have the same limits as n→∞, where \(\underline{g}_{\,k}=\min_{u\in\varDelta_{k}} g(u)\), \(\overline{g}_{k}=\max_{u\in \varDelta_{k}} g(u)\), Δ k =[,(k+1)Δ), and Δ=N/n. The usual definition of Riemann integrability over [0,∞) assumes that condition (1) of Definition 10.4.1 is satisfied and the limit of \(\int_{0}^{N} g(u)\,du\) as N→∞ exists. This approach covers a wider class of functions than in Definition 10.4.1, allowing, for example, the existence of a sequence t k →∞ such that g(t k )→∞.

References

  1. Feller, W.: An Introduction to Probability Theory and Its Applications, vol. 1. Wiley, New York (1968)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag London

About this chapter

Cite this chapter

Borovkov, A.A. (2013). Renewal Processes. In: Probability Theory. Universitext. Springer, London. https://doi.org/10.1007/978-1-4471-5201-9_10

Download citation

Publish with us

Policies and ethics