Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-26T16:59:48.931Z Has data issue: false hasContentIssue false

Convergence Rates in the Implicit Renewal Theorem on Trees

Published online by Cambridge University Press:  30 January 2018

Predrag R. Jelenković*
Affiliation:
Columbia University
Mariana Olvera-Cravioto*
Affiliation:
Columbia University
*
Postal address: Department of Electrical Engineering, Columbia University, New York, NY 10027, USA. Email address: predrag@ee.columbia.edu
∗∗ Postal address: Department of Industrial Engineering and Operations Research, Columbia University, New York, NY 10027, USA. Email address: molvera@ieor.columbia.edu
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

We consider possibly nonlinear distributional fixed-point equations on weighted branching trees, which include the well-known linear branching recursion. In Jelenković and Olvera-Cravioto (2012), an implicit renewal theorem was developed that enables the characterization of the power-tail asymptotics of the solutions to many equations that fall into this category. In this paper we complement the analysis in our 2012 paper to provide the corresponding rate of convergence.

Type
Research Article
Copyright
© Applied Probability Trust 

References

Aldous, D. J. and Bandyopadhyay, A. (2005). A survey of max-type recursive distributional equation. Ann. Appl. Prob. 15, 10471110.Google Scholar
Alsmeyer, G. and Meiners, M. (2013). Fixed points of the smoothing transform: two-sided solutions. Prob. Theory Relat. Fields 155, 165199.Google Scholar
Alsmeyer, G. and Rösler, U. (2006). A stochastic fixed point equation related to weighted branching with deterministic weights. Electron. J. Prob. 11, 2756.Google Scholar
Alsmeyer, G., Biggins, J. D. and Meiners, M. (2012). The functional equation of the smoothing transform. Ann. Prob. 40, 20692105.CrossRefGoogle Scholar
Biggins, J. D. and Kyprianou, A. E. (1997). Seneta-Heyde norming in the branching random walk. Ann. Prob. 25, 337360.Google Scholar
Fill, J. A. and Janson, S. (2001). Approximating the limiting Quicksort distribution. Random Structures Algorithms 19, 376406.Google Scholar
Goldie, C. M. (1991). Implicit renewal theory and tails of solutions of random equations. Ann. Appl. Prob. 1, 126166.Google Scholar
Jelenković, P. R. and Olvera-Cravioto, M. (2010). Information ranking and power laws on trees. Adv. Appl. Prob. 42, 10571093.Google Scholar
Jelenković, P. R. and Olvera-Cravioto, M. (2012). Implicit renewal theory and power tails on trees. Adv. Appl. Prob. 44, 528561.CrossRefGoogle Scholar
Jelenković, P. R. and Olvera-Cravioto, M. (2012). Implicit renewal theorem for trees with general weights. Stoch. Process. Appl. 122, 32093238.CrossRefGoogle Scholar
Rösler, U. and Rüschendorf, L. (2001). The contraction method for recursive algorithms. Algorithmica 29, 333.Google Scholar
Sgibnev, M. S. (2003). Systems of renewal equations on the line. J. Math. Sci. Univ. Tokyo 10, 495517.Google Scholar