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Bootstrap
techniques for measures of center for three-dimensional
rotation data
L. Katie Will and Melissa A. Bingham
Vol. 9 (2016), No. 4, 583–590
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Abstract |
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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. |
Keywords
bootstrap, 3-D rotations, mean matrix, spatial average
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Mathematical Subject Classification 2010
Primary: 62G09, 62P30
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Milestones
Received: 31 December 2014
Revised: 26 May 2015
Accepted: 31 July 2015
Published: 6 July 2016
Communicated by Mary C. Meyer
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Authors |
| L. Katie Will | |
| Department of Statistics Iowa State University Ames, IA 50011 United States |
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| Melissa A. Bingham | |
| Department of Mathematics and
Statistics University of Wisconsin-La Crosse 1725 State Street La Crosse, WI 54601 United States |
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