Adaptive and Efficient Isotonic Estimation in Wicksell's Problem

TL;DR

This paper introduces an adaptive, tuning-parameter-free isotonic estimator for Wicksell's problem, demonstrating its efficiency and optimality in estimating the distribution of sphere radii from 2D projections.

Contribution

It develops a fully automatic, adaptive isotonic estimator for Wicksell's problem and establishes its asymptotic minimax optimality in a non-standard setting.

Findings

The estimator is adaptive to local smoothness of the distribution.

It achieves $ ext{sqrt}(rac{ ext{log} n}{n})$-rate asymptotics.

The estimator is computationally simple and efficient.

Abstract

We consider nonparametric estimation in Wicksell's problem which has relevant applications in astronomy for estimating the distribution of the positions of the stars in a galaxy given projected stellar positions and in material sciences to determine the 3D microstructure of a material, using its 2D cross sections. In the classical setting, we study the isotonized version of the plug-in estimator (IIE) for the underlying cdf $F$ of the spheres' squared radii. This estimator is fully automatic, in the sense that it does not rely on tuning parameters, and we show it is adaptive to local smoothness properties of the distribution function $F$ to be estimated. Moreover, we prove a local asymptotic minimax lower bound in this non-standard setting, with $\sqrt{\log{n}/n}$-asymptotics and where the functional $F$ to be estimated is not regular. Combined, our results prove that the isotonic estimator (IIE) is an adaptive, easy-to-compute, and efficient estimator for estimating the underlying distribution function $F$.