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 language | English |
|---|---|
| Pages (from-to) | 665-692 |
| Number of pages | 28 |
| Journal | Scandinavian Journal of Statistics |
| Volume | 29 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Jan 2002 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 10 Reduced Inequalities
Keywords
- Branching diffusions
- Kernel estimation
- Minimax estimation
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