Past exam of the mathematics course of the University of Cambridge / 2019 / ii / Paper 3 / 28J / c

The strong law of large numbers gives $S_n/n=\overline{X}\to 1/\theta$ almost surely, and hence in probability. Thereforeby the continuous mapping theorem. Thus the Bayes estimator has consistency.

It differs from the maximum-likelihood estimator bySince $S_n/n\to 1/\theta$, the numerator is $O_p(n)$ and the denominator is $O_p(n^2)$, so this difference is $O_p(n^{-1})=o_p(n^{-1/2})$. The limit in part a and Slutsky theorem now give