arXiv · 2212.05634
Elliptically symmetric distributions for directional data of arbitrary dimension
Abstract
We formulate a class of angular Gaussian distributions that allows different degrees of isotropy for directional random variables of arbitrary dimension. Through a series of novel reparameterization, this distribution family is indexed by parameters with meaningful statistical interpretations that can range over the entire real space of an adequate dimension. The new parameterization greatly simplifies maximum likelihood estimation of all model parameters, which in turn leads to theoretically sound and numerically stable inference procedures to infer key features of the distribution. Byproducts from the likelihood-based inference are used to develop graphical and numerical diagnostic tools for assessing goodness of fit of this distribution in a data application. Simulation study and application to data from a hydrogeology study are used to demonstrate implementation and performance of the inference procedures and diagnostics methods.
Explore related subjects
Keep this discovery
Zehao Yu, Xianzheng Huang. 2022-12-12. Elliptically symmetric distributions for directional data of arbitrary dimension. https://arxiv.org/abs/2212.05634
Cite the original work for its findings. Save a collection to share your selection of sources.