One-sample Bayes inference for symmetric distributions of 3-D rotations

Authors:
Yu Qiu;Daniel J. Nordman;Stephen B. Vardeman
Affiliations:
-;-;-
Venue:
Computational Statistics & Data Analysis
Year:
2014

Citing 3
Cited 0

A statistical model for random rotations

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Finite-sample investigation of likelihood and Bayes inference for the symmetric von Mises-Fisher distribution

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Abstract

A variety of existing symmetric parametric models for 3-D rotations found in both statistical and materials science literatures are considered from the point of view of the ''uniform-axis-random-spin'' (UARS) construction. One-sample Bayes methods for non-informative priors are provided for all of these models and attractive frequentist properties for corresponding Bayes inference on the model parameters are confirmed. Taken together with earlier work, the broad efficacy of non-informative Bayes inference for symmetric distributions on 3-D rotations is conclusively demonstrated.