Description Usage Arguments Details Value Author(s) References
Calculating the considered log likelihood.
1 | pen.log.like(penden.env, cal=FALSE, temp=FALSE)
|
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 |
if TRUE, the iteration for optimal weights is still in progress and the temporary weights are used for calculation. |
The calculation depends on the estimated weights b, the penalized
hierarchical B-splines Phi and the penalty paramters lambda.
\eqn{l(beta,lambda)=sum(log(Φ(u_i)b))-0.5*b^T \tilde{P}(λ) b}
with
\boldsymbol{P}(λ)=∑_{j=1}{p}λ_j\boldsymbol{P}_j
The needed values are saved in the environment.
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.
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.
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