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Non-parametric estimation of the death rate in branching diffusions

  • Johannes Gutenberg University
  • Laboratoire de Probabilités et Modèles Aléatoires
  • Université de PARIS XII

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

We consider finite systems of diffusing particles in ℝ with branching and immigration. Branching of particles occurs at position dependent rate. Under ergodicity assumptions, we estimate the position-dependent branching rate based on the observation of the particle process over a time interval [0, t]. Asymptoties are taken as t → ∞. We introduce a kernel-type procedure and discuss its asymptotic properties with the help of the local time for the particle configuration. We compute the minimax rate of convergence in squared-error loss over a range of Hölder classes and show that our estimator is asymptotically optimal.

Original languageEnglish
Pages (from-to)665-692
Number of pages28
JournalScandinavian Journal of Statistics
Volume29
Issue number4
DOIs
Publication statusPublished - 1 Jan 2002
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

Keywords

  • Branching diffusions
  • Kernel estimation
  • Minimax estimation

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