Translator Disclaimer
2019 Convergence of the population dynamics algorithm in the Wasserstein metric
Mariana Olvera-Cravioto
Electron. J. Probab. 24: 1-27 (2019). DOI: 10.1214/19-EJP315

Abstract

We study the convergence of the population dynamics algorithm, which produces sample pools of random variables having a distribution that closely approximates that of the special endogenous solution to a variety of branching stochastic fixed-point equations, including the smoothing transform, the high-order Lindley equation, the discounted tree-sum and the free-entropy equation. Specifically, we show its convergence in the Wasserstein metric of order $p$ ($p \geq 1$) and prove the consistency of estimators based on the sample pool produced by the algorithm.

Citation

Download Citation

Mariana Olvera-Cravioto. "Convergence of the population dynamics algorithm in the Wasserstein metric." Electron. J. Probab. 24 1 - 27, 2019. https://doi.org/10.1214/19-EJP315

Information

Received: 11 July 2018; Accepted: 2 May 2019; Published: 2019
First available in Project Euclid: 21 June 2019

zbMATH: 07088999
MathSciNet: MR3978211
Digital Object Identifier: 10.1214/19-EJP315

Subjects:
Primary: 60J80, 65C05

JOURNAL ARTICLE
27 PAGES


SHARE
Vol.24 • 2019
Back to Top