Estimation of Parameters in Multivariate Wrapped Models for Data on a p-torus
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.
Nodehi, Anahita; Golalizadeh, Mousa; Maadooliat, Mehdi; and Agostinelli, Claudio, "Estimation of Parameters in Multivariate Wrapped Models for Data on a p-torus" (2021). Mathematical and Statistical Science Faculty Research and Publications. 109.