Models for generalized spherical and related distributions
John P Nolan

TL;DR
This paper introduces a flexible multivariate generalized spherical distribution model with star-shaped level sets, along with algorithms for simulation and implementation in an R package, enabling advanced geometric and statistical analysis.
Contribution
It develops a new model for multivariate generalized spherical distributions with star-shaped level sets and provides algorithms for simulation, implemented in an R package.
Findings
Successful implementation of the model in R package gensphere
Development of a novel tessellation simulation algorithm
Applicability of techniques to other geometric problems
Abstract
A flexible model is developed for multivariate generalized spherical distributions, i.e. ones with level sets that are star shaped. To work in dimension above 2 requires tools from computational geometry and multivariate numerical integration. In order to simulate from these star shaped contours, an algorithm to simulate from general tessellations has been developed that has applications in other situations. These techniques are implemented in an R package gensphere.
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Taxonomy
TopicsSoil Geostatistics and Mapping · Bayesian Methods and Mixture Models · Statistical Methods and Bayesian Inference
