The smoothing parameters is selected by the method of Geenens et al. (2017). It uses principal components for the rotation matrix and selects the nearest neighbor fraction along each principal direction by approximate least-squares cross-validation.
bw_tll_nn(udata, deg)data.
degree of the polynomial.
A list with entries:
Brotation matrix,
alphanearest neighbor fraction (this one is multiplied
with mult in kdecop()),
kappacorrection factor for differences in roughness along the axes,
see Geenens et al. (2017).
Geenens, G., Charpentier, A., and Paindaveine, D. (2017). Probit transformation for nonparametric kernel estimation of the copula density. Bernoulli, 23(3), 1848-1873.