Orientation Statistics Without Parametric Assumptions
针对3×2或3×3方向数据，通过将数据转换为无符号四维方向并利用样本惯性矩阵谱分解的抽样性质，提出了一种避免复杂似然方程的替代方法，计算简单，并应用于向量心电图数据。
SUMMARY Maximum likelihood estimation using the matrix von Mises-Fisher distribution in orientation statistics leads to unacceptably complicated likelihood equations, essentially because of the inconvenient form of the normalizing constant in the probability distribution. For the case of 3 × 2 or 3 × 3 orientations, the main cases of practical importance, an alternative approach is developed here by transforming the data into unsigned four-dimensional directions and using known results on the sampling properties of the spectral decomposition of the resulting sample moment of inertia matrix. It is demonstrated that the necessary computations are relatively simple by applying some of the techniques to a set of vectorcardiogram data.