A Monte Carlo simulation of the determination of mean particle volume using the Cavalieri estimator
β Scribed by Ilan Hammel; David Lagunoff
- Publisher
- John Wiley and Sons
- Year
- 2002
- Tongue
- English
- Weight
- 117 KB
- Volume
- 47
- Category
- Article
- ISSN
- 0196-4763
No coin nor oath required. For personal study only.
β¦ Synopsis
Abstract
Background
A common morphometric problem is the determination of an estimate of the size of biological particles obtained from measurements made on a sample of profiles observed in sections. Results are reported typically in terms of mean caliper diameter or mean volume of the particle.
Methods
We have investigated the use of the Cavalieri estimator for obtaining estimates of mean particle volume using a Monte Carlo simulation. Samples of spherical and ellipsoidal particles were generated by computer and serially sectioned at a fixed mean thickness with a small, imposed random variation. The area of each profile was determined and the volume of the particle was calculated according to the Cavalieri estimator. The influence on the estimate of the mean particle volume and its 95% confidence interval was evaluated for several variables: the shape of the particles, the standard deviation of the particle volume in the population, the section thickness, and the standard deviation of the section thickness.
Results
The results obtained with the Cavalieri estimator correspond favorably with those obtained with previously reported alternative methods. This leads to a recommendation for the strong consideration for the use of the Cavalieri estimator in cases in which it is technically feasible to obtain at least three sections through the individual particles. Graphs are provided, which relate the confidence interval for the mean volume to the number of particles measured. Cytometry 47:138β141, 2002. Β© 2002 WileyβLiss, Inc.
π SIMILAR VOLUMES
## SUMMARY Although the concentration index (CI) and the health achievement index (HAI) have been extensively used, previous studies have relied on bootstrapping to compute the variance of the HAI, whereas competing variance estimators exist for the CI. This paper provides methods of statistical in
In Monte Carlo simulations of polymeric chains, the chains are mast often represented as spheres, or cylinders with flat ends. In this methodological paper, we adopt a representation of the chains as spherocylinders (continuous cylinders ending in semispheres). With such a representation the testing