hierarch.bs: Construction of the hierarchical B-spline density basis.

In pencopulaCond: Estimating Non-Simplified Vine Copulas Using Penalized Splines

Description

Construction of the hierarchical B-spline density basis.

Usage

hierarch.bs(x, d, plot.bsp, typ, penden.env, int=FALSE)

Arguments

x	Marginal data for construction.
d	Hierarchy level of the marginal hierarchical B-spline density.
plot.bsp	Default = FALSE. If TRUE, each B-spline basis is plotted.
typ	typ==1 without open B-splines at the boundary typ==2 with open B-splines at the boundary.
penden.env	Containing all information, environment of pencopula().
int	Default = FALSE. If TRUE, the integral of the hierarchical B-spline density basis is calculated (used for the distribution function of the estimation).

Details

First, the marginal hierarchical B-spline density basis is constructed for each covariate 'B.tilde'.

After the construction of each marginal basis, the hierarchical B-spline density basis is built in the main program pencopula(), using an object 'Index.basis.D' (saved in the environment). 'Index.basis.D' notes which compenent of the marginal basis has to be selected. In the main program the object 'tilde.Psi.d.D' is constructed. D refers to the maximum hierachy level and 'd' is the hierarchy level of the marginal hierarchical B-spline.

Value

B.tilde	'B.tilde' is the hierarchical B-spline density basis, returned by 'hierarch.bs'.
int.B.tilde	If 'int=TRUE', the integral of the hierachical B-spline density basis is calculated and returned by 'hierarch.bs'.

Author(s)

Christian Schellhase <[e-mail]>

References

Estimating Non-Simplified Vine Copulas Using Penalized Splines, Schellhase, C. and Spanhel, F. (2017), Statistics and Computing.

pencopulaCond documentation built on May 1, 2019, 7:56 p.m.