Maximum Likelihood Estimation of Nonnegative Trigonometric Sum Models Using a Newton-like Algorithm on Manifolds
arXiv:1010.6098 · doi:10.1214/10-EJS587
Abstract
In Fernández-Durán (2004), 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.
arXiv comment9 pages 1 figure
Cited by in corpus (3)
- Exact risk improvement of bandwidth selectors for kernel density estimation with directional data
- Test of Bivariate Independence Based on Angular Probability Integral Transform with Emphasis on Circular-Circular and Circular-Linear Data
- Multivariate Nonnegative Trigonometric Sums Distributions for High-Dimensional Multivariate Circular Data