Quasi-stationary distributions and resilience: what to get from a sample?

DOI10.5802/JEP.132zbMath1459.60151arXiv1906.05635OpenAlexW3036428799MaRDI QIDQ2208627

Pierre Collet, Servet Martínez, Sylvie Méléard, Jean Rene Chazottes

Publication date: 3 November 2020

Published in: Journal de l'École Polytechnique -- Mathématiques (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1906.05635

zbMATH Keywords

dynamical systemfluctuation-dissipation relationquasi-stationary distributionbirth-and-death processempirical estimatorsengineering resilience

Mathematics Subject Classification ID

Interacting random processes; statistical mechanics type models; percolation theory (60K35) Population dynamics (general) (92D25) Applications of continuous-time Markov processes on discrete state spaces (60J28)

Related Items (1)

Strong Gaussian approximation of metastable density-dependent Markov chains on large time scales

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• On time scales and quasi-stationary distributions for multitype birth-and-death processes
• Sharp asymptotics for the quasi-stationary distribution of birth-and-death processes
• Computational Methods for Linear Matrix Equations

This page was built for publication: Quasi-stationary distributions and resilience: what to get from a sample?