A Mixing Distribution Approach to Estimating Particle Size Distributions.
Abstract
Spherical particles are dispersed randomly in a three-dimensional body. The centers of the spheres are distributed according to a dilute Poisson process. The radii of such spheres have a distribution G independent of everything else. A random probe (line, plane or thin slice) is cut through the volumes. Taking the viewpoint of nonparametric estimation of mixing distributions, we propose a new procedure that deals with the shortcomings of the classical procedures. We consider linear, planar and thin slice data. In all three cases, our approach performs better than the classical procedure. In addition, we prove consistency results. In the random plane case, we discuss the right way and the wrong way to bootstrap the distribution of a stereological estimate, corresponding to whether we have taken the structure of the problem into account or not. In the thin slice case, when G is mixed or discrete, the formulas involve a decomposition of H into its continuous and discrete component. This makes the estimation problem more complicated but also more interesting especially in the discrete case. We propose a few procedures which involve a decomposition of the data corresponding to that of H.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 19, 1982
- Accession Number
- ADA120687
Entities
People
- Anthony Yung C. Kuk
Organizations
- Stanford University