On the statistics of branching processes
Teoriâ veroâtnostej i ee primeneniâ, Tome 20 (1975) no. 3, pp. 623-633
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Let $\mu_t(n)$, $t=0,1,2,\dots,$ be a Galton–Watson process, starting from $n$ particles. We show that when $n,t\to\infty$ the estimator $$ \widehat A_t(n)=\frac{\sum_{k=1}^t\mu_k(n)}{\sum_{k=0}^{t-1}\mu_k(n)} $$ for the expectation $A=\mathbf E\mu_1(1)$ is consistent and asymptoticaly unbiased. We obtain limit distributions for $\widehat A_t(n)$ in the subcritical, critical and supercritical cases.