Abstract
Bootstrapping is a nonparametric statistical technique that can be used to estimate the sampling distribution of a statistic of interest. This paper focuses on implementation of bootstrapping in a new setting, where the data of interest are 3-dimensional rotations. Two measures of center, the mean rotation and spatial average, are considered, and bootstrap confidence regions for these measures are proposed. The developed techniques are then used in a materials science application, where precision is explored for measurements of crystal orientations obtained via electron backscatter diffraction.
Citation
L. Katie Will. Melissa A. Bingham. "Bootstrap techniques for measures of center for three-dimensional rotation data." Involve 9 (4) 583 - 590, 2016. https://doi.org/10.2140/involve.2016.9.583
Information