Title

Estimation of Parameters in Multivariate Wrapped Models for Data on a p-torus

Document Type

Article

Publication Date

3-2021

Publisher

Springer

Source Publication

Computational Statistics

Source ISSN

0943-4062

Abstract

Multivariate circular observations, i.e. points on a torus arise frequently in fields where instruments such as compass, protractor, weather vane, sextant or theodolite are used. Multivariate wrapped models are often appropriate to describe data points scattered on p-dimensional torus. However, the statistical inference based on such models is quite complicated since each contribution in the log-likelihood function involves an infinite sum of indices in Zp, where p is the dimension of the data. To overcome this problem, for moderate dimension p, we propose two estimation procedures based on Expectation-Maximisation and Classification Expectation-Maximisation algorithms. We study the performance of the proposed techniques on a Monte Carlo simulation and further illustrate the advantages of the new procedures on three real-world data sets.

Comments

Computational Statistics, Vol. 36, No. 1 (March 2021): 193-215. DOI.

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