Abstract
We consider a critical discrete-time branching process with generation dependent immigration. For the case in which the mean number of immigrating individuals tends to ∞ with the generation number, we prove functional limit theorems for centered and normalized processes. The limiting processes are deterministically time-changed Wiener, with three different covariance functions depending on the behavior of the mean and variance of the number of immigrants. As an application, we prove that the conditional least-squares estimator of the offspring mean is asymptotically normal, which demonstrates an alternative case of normality of the estimator for the process with nondegenerate offspring distribution. The norming factor is n √α(n), where α(n) denotes the mean number of immigrating individuals in the nth generation.
| Original language | English |
|---|---|
| Pages (from-to) | 1054-1069 |
| Number of pages | 16 |
| Journal | Advances in Applied Probability |
| Volume | 39 |
| Issue number | 4 |
| DOIs | |
| State | Published - Dec 2007 |
Keywords
- Branching process
- Functional
- Immigration
- Least-squares estimator
- Martingale limit theorem
- Skorokhod space
ASJC Scopus subject areas
- Statistics and Probability
- Applied Mathematics