Abstract:

Kernel density estimates for bivariate circular data are efficient non-parametric estimation methods incorporating free smoothing parameters that significantly influence the estimation process's results. In this paper, we focus our attention on selecting the optimal bandwidth for bivariate circular data from the von Mises distribution using cross-validation and a nonlinear minimized method using circular packages in R software.