Calculating the equidistant knots for the estimation. Moreover, transformation of the knots are possible.
knots.start(penden.env)
knots.transform(d,alpha = 0, symmetric = TRUE)
knots.order(penden.env)Containing all information, environment of pencopula()
Hierarchy level of the marginal hierarchical B-spline basis.
Default = 0. Alpha is a tuning parameter, shifting the knots.
Default = TRUE. If FALSE, the knots are selected without symmetry.
Selected and sorted marginal knots for the estimation.
Extended set of knots. It is needed for calculating the distribution function, help points for the integration of the B-spline density basis.
Order of the knots, corresponding to their order in the hierarchical B-spline density basis.
The knots ordered with 'k.order' for further fucntions.
Hierarchical B-Spline density basis for 'knots'.
Hierarchical B-Spline density basis for 'knots.help'.
'Knots.order' sorts the knots in the order, in which they disappear in the hierarchical B-spline basis.
Flexible Copula Density Estimation with Penalized Hierarchical B-Splines, Kauermann G., Schellhase C. and Ruppert, D. (2013), Scandinavian Journal of Statistics 40(4), 685-705.