On Posterior Asymptotic Normality and Asymptotic Normality of Estimators for the Galton-Watson Process
研究了Galton-Watson过程中未知参数θ及其后代分布均值的后验渐近正态性，并在总后代数趋于无穷时得到了均值的渐近正态性，还提出了检验过程是否超临界的方法。
SUMMARY For a Galton-Watson process with offspring distribution pθ, where θ is an unknown parameter, asymptotic posterior normality is established for θ and for the mean of the offspring distribution. A form of asymptotic normality for the mean of the offspring distribution is also obtained, without restriction on whether the process is supercritical or not, provided that the total number of offspring increases to infinity. A non-Bayesian procedure is suggested for testing for supercriticality of the Galton-Watson process.