
In this note we prove the following law of the iterated logarithm for the Grenander estimator of a monotone decreasing density: If $f(t_0) > 0$, $f'(t_0) < 0$, and $f'$ is continuous in a neighborhood of $t_0$, then \begin{eqnarray*} \limsup_{n\rightarrow \infty} \left ( \frac{n}{2\log \log n} \right )^{1/3} ( \widehat{f}_n (t_0 ) - f(t_0) ) = \left| f(t_0) f'(t_0)/2 \right|^{1/3} 2M \end{eqnarray*} almost surely where $ M \equiv \sup_{g \in {\cal G}} T_g = (3/4)^{1/3}$ and $ T_g \equiv \mbox{argmax}_u \{ g(u) - u^2 \} $; here ${\cal G}$ is the two-sided Strassen limit set on $R$. The proof relies on laws of the iterated logarithm for local empirical processes, Groeneboom's switching relation, and properties of Strassen's limit set analogous to distributional properties of Brownian motion.
11 pages, 3 figures
Strassen limit set, local empirical process, 60F15, 60F17, 62E20, 62F12, 62G20, Strong limit theorems, Functional limit theorems; invariance principles, Asymptotic distribution theory in statistics, Mathematics - Statistics Theory, Statistics Theory (math.ST), strong invariance theorem, Asymptotic properties of nonparametric inference, FOS: Mathematics, law of iterated logarithm, monotone density, Asymptotic properties of parametric estimators, Grenander estimator
Strassen limit set, local empirical process, 60F15, 60F17, 62E20, 62F12, 62G20, Strong limit theorems, Functional limit theorems; invariance principles, Asymptotic distribution theory in statistics, Mathematics - Statistics Theory, Statistics Theory (math.ST), strong invariance theorem, Asymptotic properties of nonparametric inference, FOS: Mathematics, law of iterated logarithm, monotone density, Asymptotic properties of parametric estimators, Grenander estimator
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