pen.log.like: Calculating the log likelihood

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

Description

Calculating the considered log likelihood.

Usage

pen.log.like(penden.env,cal=FALSE,temp.lam=FALSE,temp.ck=FALSE)

Arguments

penden.env	Containing all information, environment of pencopula()
cal	if TRUE, the final weights of one iteration are used for the calculation of the penalized log likelihood.
temp.lam	Calculating with temporal smoothing parameter lambda
temp.ck	Calculating with temporal weights ck of the spline basis functions

Details

The calculation depends on the estimated weights b, the penalized hierarchical B-splines Phi and the penalty paramters lambda.

Value

pen.log.like	Penalized log likelihood of the copula density.
log.like	Log-Likelihood of the copula density.

The values are saved in the environment.

Author(s)

Christian Schellhase <[e-mail]>

References

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.