Maximum likelihood estimation of nonnegative trigonometric sum models using a Newton-like algorithm on manifolds

Abstract

In Fernández-Durán [4], a new family of circular distributions based on nonnegative trigonometric sums (NNTS models) is developed. Because the parameter space of this family is the surface of the hypersphere, an efficient Newton-like algorithm on manifolds is generated in order to obtain the maximum likelihood estimates of the parameters.