Derv2: Calculating the second order derivative with and without...
In pencopulaCond: Estimating Non-Simplified Vine Copulas Using Penalized Splines

Description Usage Arguments Details Value Author(s) References

Calculating the second order derivative with and without penalty.

1	Derv2(penden.env, temp.lam = FALSE,temp.ck=FALSE,lam.fit=NULL)

`penden.env`	Containing all information, environment of pendensity()
`temp.lam`	Calculating with temporal smoothing parameter lambda
`temp.ck`	Calculating with temporal weights ck of the spline basis functions
`lam.fit`	Indicating if the iterations for a new lambda are running

We approximate the second order derivative in this approach with the negative fisher information.

`Derv2.pen`	second order derivative w.r.t. beta with penalty
`Derv2.cal`	second order derivative w.r.t. beta without penalty. Needed for calculating of e.g. AIC.

Derv2.cal and Derv2.pen are saved in the environment.

Christian Schellhase <cschellhase@wiwi.uni-bielefeld.de>

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.

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.